Norms

Analysis of the best and most efficient use of the object of assessment. Choosing the most efficient way to use the property Choosing the most efficient possible

1. Introduction

2. Determination of the most efficient use of real estate

2.1. Criteria for analysis of the most efficient use of real estate

2.1.1 Legal admissibility

2.1.2 Physical feasibility

2.1.3 Financial security

2.1.4 Maximum productivity

2.2. Basic techniques in the analysis of the best use of real estate

3. Methods for assessing the most effective use of real estate

4. Non-standard types and directions for the most efficient use of real estate

4.1. Separate uses

4.2. Intermediate uses

4.3. Legally conflicting uses

4.4. Uses other than the most efficient

4.5. Multipurpose uses

4.6. Special Purpose Uses

4.7. Speculative uses

4.8. Excessive and redundant land area

5. Conclusion

List of used literature

1. Introduction

Considering the topic by me, of course, it is very relevant in the conditions of modern market relations. The need to analyze the best and most efficient use of real estate is explained by the understandable desire of the developer to get the maximum return on investment from the project. However, if in the conditions of developed real estate markets this desire is realized in a comprehensive and comprehensive study, for the implementation of which, as a rule, an external consulting company is involved, then here the decision on the optimal use of a particular property until recently was often made on the basis of only a superficial analysis of the market, which in most cases gave the same result - housing.

It should be noted that the increase in the demand for services for the analysis of the best use in the domestic market is also due to the penetration of foreign capital both in the form of investments and loans, the carriers of which one of the mandatory conditions for the provision of financing put forward a report from an independent company that determines the best use of the facility and , respectively, confirming the most efficient investment of investment resources.

The principle of the best and most efficient use of a property is a synthesis of the principles of all three groups that were discussed above. It allows the appraiser to identify the best and most profitable option from the possible options for using the property and use it for evaluation. This principle provides for the evaluation of a piece of land, as if it were free (i.e., when evaluating an object, we are talking first of all about the highest profitability of the land plot, then about the profitability of the entire property). In this case, only those options for using real estate objects are taken into account, which:
- firstly, they comply with legal norms;

Secondly, the implementation of which is physically possible;

Third, financially feasible;

Fourthly, they provide the highest value of the property (economic efficiency).

The use case is selected in which the highest price can be paid for the object. If the site is free from buildings, then based on the most efficient use of the land, the appraiser determines which object needs to be built. If there is a structure on the site, then the appraiser determines whether to increase the value of the site by the value of the value of this structure or reduce it by the value of the cost of demolition of this structure for the selected use of the land.

The Best and Most Efficient Use Principle is a conceptual model for analyzing the various factors that affect the value of a property. This model considers important physical, legal, social and economic factors that affect the value of real estate, i.e. is, as it were, a link between all the valuation principles.

The purpose of my essay is to consider the basics of determining the most efficient use of real estate. I have been given the task of finding out by what methods the choice of the best use of the object is carried out, what analyzes are carried out for this purpose.

The abstract is presented on 27 sheets of typewritten text, including a list of used literature from 6 sources.

2. Determining the most efficient use of real estate

Since appraisal activity involves determining the market value, the analysis of the most effective use reveals the most profitable and competitive type of use of the property.

All types of property transactions based on market value require adequate evaluation and careful analysis of the economic behavior of investors and other market participants. The influence of market behavior on the financial decisions of individuals, companies, authorities dictates the concept of the most efficient use of real estate. Market factors determine market value, so the demands of market forces on properties are of great importance in determining the most efficient use.

The cost basis of any property is the value of the land. The buildings and structures located on it can be changed, but the main characteristics of the site usually remain the same. However, the income of a particular site depends on the efficiency of its use. An investor, choosing a land plot in a particular market, understands that the difference in the cost of various plots is explained by their qualitative characteristics.

The analysis of the most efficient use of the property involves a detailed study of the market situation, the characteristics of the property being valued, the identification of options demanded by the market, joint with the parameters of the property being valued, the calculation of the profitability of each option and the assessment of the value of the property for each use case. Thus, the final conclusion on the most efficient use of the property is the use of a vacant or built-up piece of land that is legally possible and appropriately designed, physically feasible, supported by appropriate financial resources and gives the maximum value.

The optimal use of a piece of land is determined by the competing factors of the specific market to which the property being valued belongs, and is not the result of the subjective conjectures of the owner, developer or appraiser. Therefore, the analysis of the choice of the most efficient use is, in fact, an economic study of market factors that are significant for the property being valued.

Market factors used to determine the best use of real estate at the valuation date are considered in the overall data collected and analyzed to determine the value of the property. Therefore, the most efficient use can be qualified as the basis on which the market value is based.

If the property being valued involves subsequent personal use or rental, then their main motivation in calculating the value will be reduced to the resulting consumer qualities of the object (income, prestige and privacy, etc.). Investment motivation, in addition to the amount of income received and capital accumulation, takes into account such arguments as tax incentives, the feasibility of the project.

Typically, best use analysis is carried out in several alternatives and includes the following areas:

Market analysis

Analysis of the feasibility of the option

Best use analysis

The listed areas of analysis involve a comprehensive study of the following issues:

Market analysis involves determining the demand for alternative use cases to the existing one in order to study supply and demand, market size, rental rate dynamics, etc. for each option.

A feasibility study involves calculating the basic components of the cost: the income stream and capitalization rates to determine the cost, taking into account the variables of each legally justified and physically feasible option.

The analysis of the most efficient use of the object involves the development of a detailed plan for the implementation of each option, considering specific market participants, the timing of the project, funding sources to select the option that ensures the maximum productivity of the assessed object.

2.1 Criteria for best use analysis

The option for the most efficient use of the property being valued must meet four criteria - these are:

Legal admissibility;

Physical feasibility;

financial security;

Maximum productivity.

The sequence of consideration of these criteria in the course of the analysis of various options for the use of real estate to select the most effective one usually corresponds to the one given above. Legal admissibility and physical feasibility are considered first, then financial security and maximum productivity are evaluated. This sequence of the analysis procedure is due to the fact that the most effective use case, even with the necessary funding, is not feasible if it is legally prohibited or its physical implementation is impossible.

The highest and best use (HUE) of a property is the most likely use of the property that is physically possible, legally permitted, economically viable, financially feasible, and results in the maximum value of the property.

Real estate is property that can be used in more than one way. Since each way of using the property corresponds to a certain amount of its value, before the assessment, one way of using is selected, called the best and most effective.

The best use opinion reflects the Valuer's opinion on the best use of the property based on market analysis. The term "highest and highest use" as used in this report means that use which, of all reasonably possible, physically feasible, financially acceptable, properly secured and legally permissible uses, results in the highest current value of the land.

The analysis of the best and most effective use is performed by checking whether the considered use cases meet the following criteria:

Legislative Permissibility: Consider uses permitted by zoning ordinances, restrictions on private initiative, historic zone regulations, and environmental laws.

Physical feasibility: Consideration of uses that are physically realistic in the locality.

Financial Feasibility: A consideration of what physically feasible and legally permitted use will generate an acceptable income for the site owner.

The criterion for financial feasibility is a positive return on invested capital, i.e. a return equal to or greater than the costs of compensation for maintenance costs, financial obligations and the return of the capital itself.

Maximum Efficiency: Considering which of the financially feasible uses will generate the maximum net income or maximum present value.

The environment, the topography of the land allows it to be used for the construction of buildings of various functional orientations - administrative, warehouse, agricultural. This does not require additional capital investments that would compensate for the physical characteristics of the study area (size and shape, topographical and geographical features, engineering-geological and hydrogeological conditions, accessibility of transport and communal amenities).

No legal conditions have been identified that limit the nature of use - legislative, municipal acts and regulatory requirements. There is no information about the expected changes in the regulations in the relevant part, which would significantly affect the nature of the use. The attitude of the local population is generally favorable.

In order to correctly use approaches to estimating the cost, as well as to answer the question of the feasibility of the continued existence of the improvements available on the site, the determination of the best use of the improvements available on the site is carried out in two stages:

For the site as free;

For a site with existing improvements.

This analysis assumes that the land is undeveloped (or can be vacated by demolition of existing buildings). Evaluation of a land plot under these conditions is necessary for the correct application of the cost method.

Analysis of the possibilities of using the site as free

When determining the most efficient use of a piece of land as free, the following are taken into account:

Purpose and permitted use;

The prevailing land use methods in the immediate vicinity of the assessed land plot;

Prospects for the development of the area in which the land is located;

Expected changes in the land and other real estate market;

Current use of the land.

However, the choice of the option of the most efficient use of land can be carried out among options that are physically possible, economically justified, complying with the requirements of the legislation, financially feasible, and as a result of which the estimated value of the value of the land plot will be maximum (the principle of the most efficient use).

If the value of the vacant lot exceeds the value of the property with improvements, the best and most efficient use would be to use the land as vacant. However, in this case the situation is different. The building as a whole, as a single piece of real estate, certainly exceeds the value of the land. In addition, the appraised premises are located inside a building owned by different owners, and therefore the owner of this premises is limited in his ability to independently use his share in the land plot. In connection with the foregoing, the land plot related to the object of assessment cannot be considered as free. Therefore, the appraiser analyzed the possible use of the site with existing improvements.

Conclusion: The location of the land plot, as well as the entire infrastructure of the area, makes it cost-effective to use it for development, commercial buildings.

Analysis of options for using the assessed object: Non-residential building

Use as production and storage facilities

The object of assessment is a non-residential building, which imposes restrictions on the possible options for its use. For example, it is unacceptable to use the premises associated with the organization of production, the technological process of which, one way or another, is associated with an increased level of noise, vibration, harmful emissions, and fire hazard. The use of premises as a warehouse is completely unjustified from the point of view of financial efficiency. Income from the lease of warehouse premises is significantly lower than the corresponding income from using it as a retail or office space. Therefore, such use cases should be abandoned.

Use of premises as commercial

An analysis of the real estate market shows that sales prices and rental rates for retail space are higher than for office space. Therefore, such use could be more efficient. At the same time, when choosing the most efficient use option, it should be taken into account that the use of premises to accommodate a full-fledged store is associated with high costs due to the need for significant redevelopment and repair. The surrounding infrastructure of the location of the appraisal object is industrial, administrative and large retail facilities. Thus, taking into account that the subject property, although located in a busy place, is not well suited for small retail trade, the financial feasibility of this option looks doubtful.

Use of the premises as a commercial object - an office building.

An analysis of the real estate market shows that a commercial building is a much more peaceful investment. The demand for commercial premises is growing along with the economy. The reason why raw material, financial and banking structures are currently actively investing in the commercial real estate market lies in the high level of profitability of office projects. With a high investment potential, Kemerovo is experiencing an acute shortage of high-quality commercial premises. In view of the foregoing, the Valuer believes that such use is the most efficient.

Conclusion: Thus, the best and most efficient use of the assessed object is to use the building as an office building.

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Choicemostefficientoptionuseobjectreal estate

Introduction

The analysis of the most efficient use of the property involves a detailed study of the market situation, the characteristics of the property being valued, the identification of options in demand by the market that are compatible with the parameters of the property being valued, the calculation of the profitability of each option and the assessment of the value of the property for each use case. The best and most efficient use of a property represents the use of a vacant or built-up piece of land that is legally possible and appropriately designed, physically feasible, supported by appropriate financial resources, and yields the highest value.

The purpose of this work is to analyze the property in terms of its best and most efficient use as conditionally free, as well as with improvements. Land plot with cadastral number 78:5516A:2 and is located in St. Petersburg at the address: Prosveshcheniya, 40, letter A. For this, legally feasible options for using the land plot will be determined based on the Land Use and Development Rules of St. Petersburg, and All necessary calculations have also been made.

1 . Characteristicsobject

This section of the work includes:

Quantitative and qualitative characteristics of the object, including information on property rights, encumbrances associated with the real estate object, on the physical properties of the real estate object, available information on wear and obsolescence.

Quantitative and qualitative characteristics of the elements that make up the real estate object, which have specific features that affect the results of the project.

Information about the current use of the real estate object.

Other factors and characteristics related to the real estate object that significantly affect the technical and economic indicators of the project.

1.1 Descriptionlandsite

The description of the land plot is presented in the table below.

Table 1.1 - Description of the land plot

Object address (city, region, district)	St. Petersburg, Prosveshcheniya avenue, 40, letter A
Owner (tenants)	State
Rights to the land	Permanent (perpetual) use, Ownership
Cadastral number
Date and price of acquisition of the object
Plot area, m2
Current use of the object	For placement of objects of culture and art
Functional zoning of the site in accordance with the General Plan	With the General Plan: "D" - a zone of all types of public and business development with the inclusion of residential buildings and engineering infrastructure facilities related to the maintenance of this zone. With PZZ: TD2-2 - a zone of specialized public and business facilities in the peripheral and suburban areas of the city, with the inclusion of engineering infrastructure facilities.
Altitude regulation, m
Location characteristic	Relief without significant slopes
Plot shape	Rectangular
Availability of utilities	electricity, gas, water, sewerage, central heating, etc.
Transport accessibility	satisfactory
Driveways	Road (asphalt)

1.2 Description of improvements

The description of the improvements is presented in the table below.

Table 1.2 - Description of land improvements

general characteristics	architectural style, constructive and space-planning solutions, type
Year of construction
Year of last overhaul
Total area, m2
Number of floors
Actual age of the building, years
Engineering support systems:	Condition - good
Water pipes
Power grids
Sewer network
Heating and cooling system



A television
Alarm (security, fire)
External landscaping:
landscaping
Car parking
Playground
street lighting

1.3 History of the object

In 1986, in the Vyborgsky district of St. Petersburg, on Prosveshcheniya Prospekt, a new beautiful building appeared, built specifically for the first Children's Art School in the city. Bright, well-equipped classrooms, spacious corridors, buffet, one exhibition and 2 concert halls. These beautiful premises housed three departments - artistic, choreographic and musical. Such a creative community was new and immediately aroused the liveliest interest not only among the residents of the microdistrict, but also among the whole city.

Rice.

In 1999, the Children's Art School was named after Georgy Sviridov, a remarkable Russian composer, whose life and work were associated with our city for many years. A truly creative atmosphere, a high professional level of education have developed largely thanks to the founder and first director of the school, Honored Worker of Culture of Russia A. M. Serdyuk (1937-2001). Alexander Mikhailovich was a wonderful teacher and musician, who perfectly mastered two instruments, the organ and the piano. His name was often found on philharmonic posters not only in St. Petersburg, but also in other cities of Russia and abroad, it was such a leader who was able to create a team of excellent specialists in their field who love their profession and strive to captivate children into the world of music, dance, painting.

Since 2001, the school has been run by Honored Worker of Culture of the Russian Federation Natalia Mikhailovna Veledeeva. Natalia Mikhailovna has been working in the field of music education since 1966, and has been in an administrative position since 1987. An experienced leader, N.M. Veledeeva enjoys great prestige in the city, is a member of the Board of Directors of Schools under the Committee for Culture.

About 2,000 children study at the school, more than 130 teachers work. For great creative achievements, the best teachers were awarded with honorary titles. "Honored Worker of Culture of the Russian Federation": N.M. Veledeeva, V.G. Efimov, M.V. Hwang, G.S. Leonov; "For achievements in culture": I.S. Sokolova, V.P. Kalshchikov; "For success in the humanization of the school of St. Petersburg": N.M. Veledeeva, V.G. Efimov, M.V. Hwang, M.F. Pugachevsky, O.I. Kuznetsova, O.F. Perevertkina, M.V. Fursova, O.V. Gerasimova, Yu.B. Slivovsky. The school is proud of its talented students, the best of which win the titles of laureates and diplomats in many international competitions and festivals. Future professionals are awarded scholarships from the Committee for Culture of the Government of St. Petersburg, the Ministry of Culture of Russia, the Philharmonic Society of St. Petersburg. The school team proudly bears the name of the great Russian composer. On December 8, 2000, in connection with the 85th anniversary of G. V. Sviridov, the school museum "Sviridov in Leningrad" was solemnly opened.

Since 2000, the school has annually hosted the Open St. Petersburg Festival of Children's Performing Arts named after A. G.V. Sviridov. In 2005, having become a member of the Association of Music Competitions of Russia, the festival acquired a new status: the International Competition for Youth Performing Arts named after G.V. Sviridov. All these years, the composer's nephew Alexander Sergeevich Belonenko has been the honorary President of the competition, and the Honored Artist of Russia, Professor of the St. ON THE. Rimsky-Korsakov Oleg Yurievich Malov.

For many laureates, the victory at the Sviridov competition was a good start in their professional development.

For the youngest musicians (up to 10 years old) the School initiated the city festival "Sparkles". Every two years, young soloists of any specialty compete in musical performance. The award ceremony and the concert of laureates takes place in the Small Hall named after M.I. Glinka of the St. Petersburg Philharmonic. Today the school plays a significant role in the concert life of the city. Students of the music and choreography departments constantly perform at large concert venues: in the Sheremetev Palace, the Great and Small Halls of the St. Rimsky-Korsakov. The guys take part in the music subscription of the House of Composers, the theater "Through the Looking Glass", in the House of Kochneva, in the museum of F.I. Chaliapin, in the palaces of the Russian Museum.

One of the best music departments is the piano department. Such teachers as: G.S. Leonova, D.Yu. Bystrov, M.Yu. Kuzmina, O.F. Perevertkina, O.I. Radaeva, M.V. Hwang successfully prepares her students for performances at competitions, city concerts and for admission to secondary schools. All departments of the school employ former graduates who returned to their native walls after graduating from higher educational institutions. The school is famous for its creative teams, which perform not only in our city, but also abroad.

An exemplary team of a brass band led by the Honored Worker of Culture of the Russian Federation Efimov V.G. - winner of many international competitions and festivals - visited Israel, Italy, Germany, France, Spain, Belgium, Greece. Choir group "Consonance" under the direction of M.V. Fursova is a laureate and diploma winner of many international festivals: I prize at the competition-festival dedicated to the 90th anniversary of G.V. Sviridova (Moscow, 2005), Diploma of the 1st degree at the Open All-Russian Children's Choir Assembly "On the banks of the Neva" (St. Petersburg, 2006), Gold medal of the international choral competition "Mundi Cantant" (Czech Republic, Olomouc, 2007), I prize of the international competition named after G.V. Sviridova (SP-b 2007), II degree diploma of the X St. Petersburg festival of children's choirs "Classics and Modernity" (2007), I prize for 56 - Europees Musikfestival voor de Jeugd Neerpelt (Belgium 2008), Silver diploma at the 6th Festival e Concorso Corale Internazionale Jesolo Lido - VENEZIA (Italy 2008). The team constantly travels with concerts to many cities in Russia and abroad: Poland, Hungary, Finland, France, Italy, the Czech Republic, Belgium. The art department of the school has 22 teachers. Among them: N.E. Belykh, V.P. Golovin, O.N. Pankratova, F.F. Rasulov, Yu.B. Slivovsky, M.S. Smirnov, N.P. Starova, M.V. Trofimova are members of the Union of Artists of the Russian Federation. The works of students of the art department have repeatedly won prizes at exhibitions in St. Petersburg, Russia, England, America, France, Germany, Finland, Poland, the Czech Republic, Hungary.

The choreographic department employs a team of experienced teachers who have extensive experience in stage and pedagogical work and participate in international seminars on choreographic art: in the USA, France, Finland. Students of the department study according to the academic program. I.K. works at the department. Novik is the leading director of the St. Petersburg Children's Musical Theater "Through the Looking Glass". Under her leadership, interesting creative work is carried out, performances are carried out that combine the activities of the choreographic, musical and artistic departments of the school. Established creative links with the Academy of Russian Dance named after A. Vaganova. Students perform at the leading concert venues in the city: the Great Philharmonic Hall, the Academic Capella, the Smolny Cathedral. One of the achievements of the department's work is the achievement by students of the titles of laureates and diplomats at city and international festivals, including: "Dancing Olympus" (Berlin 2008), "Sparks" (St. Petersburg 2009). The performances of the students greatly adorn the holding of subscription and holiday concerts.

2 .Analysisenvironmentalenvironments

2.1 Analysislocationsobject

Rice.

Territory development

The territory of the quarter in which the object under study is located is limited to:

- Yesenin Street;

- Prospect of Enlightenment;

-Ivan-Fomin street;

- Lilac boulevards.

The study area is distinguished by an abundance of parks.

The largest of them are Sosnovka Park, with a well-groomed forest, walking paths, playgrounds and volleyball courts, the Forest Engineering Academy Park, located near Muzhestva Square.

The ecological state of the residential quarters of the district is generally good, but the degree of soil pollution in microdistricts varies significantly. But the level of air pollution, in general, is higher than in the neighboring Primorsky district, where the air is actively ventilated from the bay. Also next to the investigated object is the Kantemirovsky bridge, the territory of which is considered one of the noisiest places in the city.

Figure 2.1 - Local location of the object

Residential development

The composition of the housing stock of the Vyborgsky district practically repeats the chronology of the city's development. In the south - the old fund, in the central part - "Stalinka" and "Khrushchev", in the north - mostly new houses. Among the main advantages of the Vyborgsky district is its developed infrastructure. The district ranks fourth in the ranking of St. Petersburg districts in terms of the availability of high-quality retail space. The area is known for shopping areas near the Udelnaya and Politekhnicheskaya metro stations, Svetlanovsky and Shuvalovsky shopping centers, huge shopping and leisure centers in the Ozerkov area and Prospekt Prosveshcheniya metro station, O Kay, Lenta hypermarkets "and" Maksidom". In the area there are business centers "Nobel" (Pirogovskaya embankment), "Aquatoria" (Vyborgskaya embankment), "Bekar" (B. Sampsonievsky prospect). It should be noted that most of the existing business centers are located on Vyborgsky side.Vyborgsky district has a large number of objects (over 40), renting office space.Also, the area is reconstructing old buildings, designing and building new buildings for business centers. parking lots.

general information

The Vyborgsky district (founded in 1718) is one of the largest in St. Petersburg today, and one of the oldest: it got its name back in 1817. It was at this time that by decree of Peter I, the territory along the right bank of the Bolshaya Nevka and the Neva, where the ancient road to Vyborg passed, began to be called the Vyborg side.

In the early years of the city's existence, the Vyborg side was considered a frontier. At the forefront of the city, this territory was part of the St. Petersburg part, then became an independent Finnish, then Vyborg side.

On the right bank of the Bolshaya Nevka, which was almost not flooded during floods, already at the beginning of the 18th century they began to build warehouses, barns, and hospitals. The embankment in this section was constantly expanding due to the backfilling of the bank and advanced into the river by almost 200 meters. Since 1711, residential buildings appeared. Builders of the city, retired soldiers, artisans settled here. This is how settlements were formed: cooperage, companionship, hospital, Sinyavinskaya. Here, built-up areas alternated around the factories. In the first quarter of the 18th century, the Vyborg side was being developed more slowly than other districts of St. Petersburg. In 1717, there were only 350 households on the Vyborg side (there were 1,720 households on the Admiralteysky Island in the same period).

Various industrial enterprises appear on the outskirts - sugar, tanneries, breweries; shipyard, barracks, prisons. Right there on the embankments of the Neva, tsarist dignitaries - G. Teplov, A. Bezborodko, Admiral A. Sinyavin and others are building summer cottages.

The southern part of the district, adjacent to the Neva, became part of the city in the 18th century. A hospital settlement was formed here. The first military hospital in Russia (Admiralteyskaya Hospital) was founded in 1715 by decree of Peter I, next to it in 1717 a land military hospital was opened. They were built on piles by the first architect of our city D. Trezzini, then in stone these buildings with two turrets in the corners and almost 300 meters long were rebuilt by M. Zemtsov. The form that we are seeing now, the Academy acquired in the 60s of the last century. First, those buildings that overlook the Neva were rebuilt, then the rest. Since 1881, this complex has become known as the Military Medical Academy. In the second half of the 19th century, an industrial region was formed along the banks of the Neva and Bolshaya Nevka. The factories of A. Baranovsky, G. Lessner, L. Erikson, L. Nobel, as well as Sampsonievskaya, Nikolskaya and Vyborgskaya manufactories are located here.

The central part of the modern district was previously called "Forest". It is rather difficult to determine the exact boundaries of Lesnoy in a modern city. Sergei Alexandrovich Bezbakh (an outstanding local historian of the 1920s) noted in his book that “Forest” is the name given to the area on the right side of the Vyborg highway (Engels Ave.) between Lanskaya st., Isakov per. (now Manchesterskaya St.), Staro-Pargolovsky Ave. (nowadays Maurice Thorez Ave.), Theological Cemetery and the Park of the Forestry Institute. Now, according to the historian S. Glezerov: “The broad concept of “Forest” includes the nearby Malaya and Bolshaya Kushelevka, Grazhdanka and Sosnovka.”

Lands in the central and northern part of the modern Vyborgsky district used to belong to the royal nobles - Shuvalov, Levashov, Kushelev. Their names gave the name to the villages of Kushelevka, Levashovo, Shuvalovskoe. In the 19th century, the Forestry School moved from Tsarskoye Selo to the Kushelevka area, on the basis of which the Forestry Engineering Academy was subsequently created. In the middle of the 19th century, the area near the Forest School began to be built up with dachas, but with the laying of a branch of the Finnish Railway in the 70s, their construction moved to the north, to Shuvalovo and Ozerki. In the area of Muzhestva Square, all the main highways of Lesnoy are connected. In the 18th century, they led to the Spassky Manor. Then it was owned by an influential nobleman of the royal court of Catherine II and Paul I - Ivan Kushelev. Having bought part of the land from Count Bezborodko, he built a summer residence. At the beginning of the century, next to Kushelev's dacha, there was an English farm, whose history dates back to the reign of Alexander I, when he allowed the retired English captain Davidson to set up an exemplary agricultural farm, for which land beyond the Vyborg side was acquired, including part of the Spasskaya manor. The farm did not become a role model, but brought only losses and in 1809 was returned to the treasury. Part of the farm's land was sold, except for two plots where outbuildings were located. In 1811, the Forest Institute, transferred from Tsarskoe Selo, was located on them, then called the “Forst Institute” (from the English “forest” - forest), which later gave the name to the entire area. The Institute gradually turned part of its land into a forest park: instead of the old crooked roads to the Spassky Manor and Murino, streets were laid, pine trees were planted, nurseries, a botanical garden, and a greenhouse were arranged.

From the 30s of the XIX century, the institute, in need of money, began to sell part of its land to private individuals for the construction of summer cottages, and the area around it became a busy suburb. The lands were quickly bought up by wealthy Petersburgers, who appreciated the attractiveness of these suburban places. The resulting dacha area began to be called "dachas behind the Forest Institute." Then, when the institute in 1837 became a military educational institution, which was called the Forest Corps, and the area began to be called the Forest Corps. The name survived until the middle of the 19th century, later the word "corps" gradually fell out of use and the name "Forest", and sometimes "Forest" remained.

Over time, by the beginning of the 20th century, the name "Forest" covered a fairly large territory. When the Polytechnic Institute was opened here, the importance of Lesnoy increased especially. It turned into a kind of St. Petersburg "Cambridge". The fate of Lesnoy after the revolution is typical for many metropolitan suburbs. “In the 20-30s of the XX century, a simple public from among the workers and co-employees lived here, and in the 60s the city came here,” writes S. Glezerov. Only a few buildings have survived from the old Lesnoy, among them - the wooden building of Bertling's dacha on Bolotnaya Street, famous for its revolutionary past, now there is the Children's Historical Museum, Kotlov's mansion on Muzhestva Square, the house of Professor of the Forestry Institute Dmitry Nikiforovich Kaygorodov near Serebryany Pond, a mansion near the square Courage, which the old-timers call "the house of Chaliapin." And today the park of the Forestry Academy (formerly the Forest Institute), as before, is a favorite place for walking for residents of the Vyborg region. The most ancient of the northern environs of the region is the village of Pargolovo. The first mention of it is found in the census salary book for Novgorod for 7008 (1500). Then the village was called Parkola. The Pargolovskaya manor, donated by Peter I to his daughter Elizabeth Petrovna, included the following settlements: Suzdalskaya Sloboda (1st Pargolovo), Malaya Vologodskaya Sloboda (2nd Pargolov). The district has existed on the borders since 1978, it borders on Primorsky, Kalininsky, Petrogradsky, Central. In the north, the district borders on Vsevolozhsky and Kurortny districts. In the south, its border runs along the Neva between Liteiny Bridge and Bolshaya Nevka, Vyborgsky is connected to the Central District by the Liteiny Bridge, which thrown across the Bolshaya Neva.

The territory of the district stretched out in the direction from the Vyborgskaya embankment and expanded to the north. The area of the territory is 11.5 thousand hectares. The population is about 412 thousand people. In terms of population, the district ranks third in the city after the Kalininsky and Nevsky districts.

Despite the fact that the Vyborgsky District occupies one of the leading places in the city in terms of saturation with industrial enterprises, it is one of the greenest areas of St. Petersburg. More than a third of the district is occupied by parks and squares. For example, the area of the Sosnovka park is about 322 hectares. The territory of the park of the Forestry Academy - 65 hectares, green spaces in Levashovo - 346 hectares. By the amount of greenery per capita, the district ranks first in St. Petersburg.

The industrial zone along the Bolshaya Nevka still exists. There are more than fifteen large enterprises in the territory, including "Engine", "Maison", "Uranus", "Petersburg Textile", "System", "Red Thread", "Compressor", "Red Mayak", "Teplopribor", "Svetlana", the first confectionery plant "Azart", etc. In the post-Soviet period, most of the industrial production on the territory of the Vyborg side was closed. The idea arose to create a large business center in their place. Large investment projects are being implemented at a rapid pace - the Nissan and Hyundai automobile plants are being built, the first stage of the Petmol dairy plant (Unimilk group of companies), the Capital-M business center on Matrosova Street, the company's customs and logistics terminal "Sterkh" in Pargolovo.

In Soviet times, another industrial zone, Parnassus, appeared in the north of the Vyborgsky District, where industrial construction continues today. It houses such large enterprises as Baltika Brewery OJSC, Parnas-M CJSC. Among them, in addition to those already mentioned above, are the Parnassus Pilot Plant for Metal Structures, an asphalt-concrete plant, LPO Vibrator, Enterprise No. 2 Petrochimopttorg, Pepsi-Cola, Wimm Bill Dann. The Northern Customs Post, warehouses and terminals are also located here. There is also a business center of the same name on Parnassus. Concrete garages of collective parking lots lined up along the railway and Engels Avenue. The industrial zone "Parnassus" continues to develop rapidly, developing the territories around it, crawling beyond the Ring Road.

Transport accessibility of the Vyborgsky district can be generally described as satisfactory.

Its central part is served by two metro stations - "Lesnaya" and "Vyborgskaya", the northern part - by four stations: "Parnas", "Prospect of Enlightenment", "Ozerki", "Udelnaya". However, the territory of the district is too large, the existing metro stations are clearly not enough. The main thoroughfares of the district, connecting its northern and southern parts, are: Bolshoy Sampsonievsky Prospekt, Engels Prospekt and Vyborgskoye Highway, as well as Lesnoy, Tikhoretsky Prospekts and Kultury Prospekt, which connect the northern and southern parts of the district. The western and eastern parts of the district are connected by Svetlanovsky, Lunacharsky, Prosveshcheniya, Suzdalsky avenues. Owners of personal vehicles, leaving the area to the city center, are forced to stand idle in long traffic jams. The existing interchanges at the exit from the northern regions cannot cope with the load, and at rush hour vehicles "stop" on Muzhestva Square, Svetlanovskaya Square and Lenin Square.

the immediate surroundings of the object - mainly manufacturing companies and residential buildings

· the level of intensity of traffic flows near the Object of Assessment is high, and the level of pedestrian activity is medium;

· transport accessibility by public transport and automobile is characterized as good satisfactory.

3. Analysismarketcommercialreal estate

immovable commercial property

Overview of commercial real estate. Commercial real estate traditionally includes segments of office, retail, industrial and warehouse and hotel real estate. At the same time, retail real estate includes areas used for the placement of various services: catering, household, sports, entertainment, etc.

In accordance with the preliminary positioning of the appraised property, this Report provides an overview of commercial real estate in St. Petersburg in the following sectors:

Industrial and warehouse real estate;

Office real estate;

Land.

General situation. In the commercial real estate segment, progressive development is taking place: the share of unoccupied space is decreasing, rental rates are growing in parallel with inflation. Analysts of all companies agree on this. Experts from various companies estimate the total supply of high-quality office space at about 2 million square meters. m. The most stingy estimates - in the company Knigh Frank St-Petersburg (1.65 million), more generous than others in this regard, the specialists of the management company Maris / CBRE (2.2 million). All experts also agree that over the past the number of vacant premises in the office segment has decreased over the past year (the current level of vacancies in companies is estimated at 11-13%). At the same time, Jones Lang LaSalle experts in St. Petersburg note that the St. Petersburg office real estate market in 2011 remained a “tenant market”, while net absorption exceeded commissioning, as well as a decrease in the share of vacant space in 2012 from 19.7% to 13 ,5.

Stable demand for office space, a decrease in the number of vacant premises led to an increase in rental rates. According to Maris analysts, class B offices have risen in price by 3-4%. In existing class A office centers, rental rates did not change significantly.

Experts estimate the current level of occupancy of retail space in a similar way - about 96% - which indicates a high degree of demand for this type of real estate in the city. Despite the modest share of vacant space, there is no rapid growth in rates in this segment either. Trading places over the past year have risen in price about the same as offices - by 7-10%.

In 2012, there was almost no increase in the warehouse market (increase at the level of 1% of the available volume). Because of this, the occupancy of these areas has increased significantly, developers urgently launched frozen projects. At the end of 2012, the values of capitalization rates in St. Petersburg are: for high-class office properties - 9.5-10%, for high-quality retail properties - 10-10.5%, for institutional quality assets in the warehouse real estate segment - 11-11 ,5%. In the regions, the minimum capitalization rates for high-end commercial real estate have also undergone a slight downward correction.

Table 3-1 Minimum capitalization rates for quality commercial real estate in 2012

The development of commercial real estate segments in St. Petersburg is uneven. The most developed markets are office and retail real estate. The market of hotels and production and storage facilities lags far behind them.

Territorial distribution of commercial areas. The territorial distribution of commercial space is highly dependent on their function. Office premises, both in business centers and built-in, as well as hotel facilities are mainly located in the central districts of St. Petersburg - Admiralteisky, Petrogradsky, Central. This is due to the proximity to business centers and tourist destinations.

Large shopping complexes are mainly located in residential areas (Primorsky, Vyborgsky, Moskovsky), which is determined by the presence of large land plots there and proximity to the bulk of consumers. Built-in retail premises are located mainly in the central districts (Admiralteisky, Vasileostrovsky, Petrogradsky, Centralny). High-quality production and warehouse complexes gravitate towards the main transport corridors of the city - the Sea Port of St. -10, direction to Moscow), Murmansk highway (M-18) and the western corridor (Tallinskoe highway, M-11).

According to GUION, built-in industrial and warehouse premises for rent are mainly located in Vyborgsky, Nevsky, Krasnogvardeisky, Frunzensky and Kirovsky districts.

Market activity. According to analysts from the Center for Appraisal and Consulting of St. Petersburg, there is some redistribution of forces in the investment segment and development in the market - there is a “change of composition” due to the previous crisis. Since the second half of 2012, there has been a noticeable and rather sharp increase in the activity of buyers in the market due to individuals and legal entities interested in acquiring relatively large commercial real estate (primarily buildings) for various purposes - retail, office, leisure and entertainment. This trend is largely due to the fact that Russia and, in particular, St. Petersburg in 2011 finally overcame the crisis and entered the real estate market on a stable growth rate.

On the other hand, the global economy and financial markets continue to be in a fever due to well-known events in the US and Europe. This gives investors a certain lack of confidence in the future and rather serious inflationary expectations. In this situation, customers have a motivation to purchase existing facilities that have already been built and filled with tenants. Such real estate serves as an instrument for investing funds and insuring yourself against depreciating money. Indeed, according to the experience of 2008-2009, good quality properties filled with tenants, although they showed a slight decrease in current indicators in terms of occupancy and profitability, continued to generate cash flow.

In addition to investors, end buyers have become quite noticeably more active. This can be attributed both to the stabilization of the economy and the process of transferring the offices of a number of large companies to St. Petersburg, primarily in the commodity sector. Very often, the strategy of such companies is not renting, but owning real estate. They are focused on acquiring modern high-class buildings in the best places in the city and are ready to pay the appropriate price for them. In 2012, the real estate market was replenished with offers. The consequence of the crisis was that a number of owners, for one reason or another, put their objects up for sale. In addition, it was in 2012 that collateral objects of banks began to be sold. Banking structures came to that critical point when it was necessary to make a decision regarding such assets. And often it was in favor of the sale, although sometimes at a significant discount. It should be noted that high-quality objects with a good location and level of construction are rare in this pledged mass. Now buyers who are closely monitoring the current situation have the opportunity to enter into negotiations with banks and buy out these collateral assets.

In general, the activity that began in the summer of 2012 has already led to some significant transactions for the market. For example: Jensen Group's acquisition of the Passage department store as a collateral asset, the sale of the Coliseum cinema, negotiating the sale of the Gallery shopping center and a number of completed or open transactions with famous buildings in the city. This trend of the autumn-winter period will continue.

At the moment, there is some redistribution of forces in the investment segment and development. Some companies are strengthening their influence, others are losing ground or leaving the market, and new players are also emerging.

If there are no global financial shocks in the future, then by the end of 2012 we will observe a fairly confident growth of the market - both rental and investment transactions.

Table 3-2. Return on investment in various segments of commercial real estate in St. Petersburg

Consumer market. In January-November 2012, compared to the same period last year, the retail trade turnover in the city increased by 8.3%, in the region - by 2.7%. The turnover of public catering in the city increased by 2.4%, in the region - by 7.9%. The turnover of wholesale trade in comparison with the same period of the last year in the city decreased by 10%, in the region it increased by 1.7%.

Labor market. In October 2012, compared to October 2011, the number of jobs substituted in organizations (excluding small businesses) increased by 1.0% in St. Petersburg, by 0.1% in the Leningrad Region. According to the labor and employment committees of the population of St. Petersburg and the Leningrad Region, the number of officially registered unemployed from November 2011 to November 2012 decreased in the city by 22%, in the region - by 16% and amounted to 10.2 and 4.2 thousand at the end of November 2012, respectively. . Human. The level of registered unemployment at the end of November 2012 was 0.4% in St. Petersburg, 0.5% of the economically active population in the Leningrad region, against 0.5%, both in the city and in the region at the end of November 2011.

Construction and investment. In January-November 2012, the volume of investments in fixed assets by large organizations in St. Petersburg decreased by 10.0% compared to January-November last year and amounted to 176.2 billion rubles, in the Leningrad Region it increased by 4.0% and amounted to 194.1 billion rubles. Since the beginning of the current year, the volume of work in the type of activity "construction" in St. Petersburg also decreased by 6.7% compared to the corresponding period last year and amounted to 299.4 billion rubles, in the Leningrad Region it increased by 10.1% and amounted to 101.4 billion rubles.

The commissioning of residential buildings in January-November of the current year, both in St. Petersburg and in the Leningrad Region, increased by 2.8% and 11.3%, respectively, compared to the corresponding period last year and amounted to 1,778.3 thousand square meters . m of living space in St. Petersburg and 894.0 thousand square meters. m. in the Leningrad region. In November this year. in St. Petersburg, the production building of LLC Ferromet-Invest, the production and warehouse complex of LLC Trader, the production and technical center for the repair and sale of cars of LLC Phoenix-Motors, the warehouse complex with a parking lot of CJSC UNISTO were put into operation, a building materials warehouse of GRAN CJSC, 1 transformer substation, 3 gas stations, a preschool educational institution in the Pushkinsky district, a restaurant in the Kurortny district, a business center in the Moskovsky district, a social and amenity complex in the Kirovsky district, and others.

In the Leningrad Region, a greenhouse facility was put into operation by LLC Vector, a selection and seed center of the Forestry Department of the Leningrad Region, a wood processing workshop by LLC Pallet-Plus, 2 boiler houses in the Vyborgsky and Vsevolozhsky districts, 1 gas station, a preschool educational institution and a federal training center (stage 1) in the Vsevolozhsk region and others.

4. Analysisthe bestAndmostefficientuselandsiteHowconditionallyfree

Choosing the optimal use of the land.

An analysis in order to select the best and most efficient use of land is usually performed in two cases: if a separate assessment of a piece of land is necessary, and also when selecting objects for comparative analysis. The concept of “best and most efficient use” is defined as the probable use of the property being assessed with the maximum return, and the conditions for the physical, legal, and financial feasibility of such actions are indispensable. First, you need to list the functions that can be implemented on this piece of land without any restrictions. The most effective use is determined by the interaction of a number of factors:

Legal feasibility: Consider uses permitted by zoning ordinances, private initiative restrictions, historic site regulations, and environmental laws

Physical feasibility: Consideration of uses that are physically realistic in the locality.

financial feasibility. Consideration of the fundamental possibility of providing financing for the project with the involvement of borrowed capital.

Maximum efficiency. Considering which of the economically viable uses will generate the maximum net income or maximum present value

Analysis of the use of the site as conditionally free. legal feasibility. The main, auxiliary and conditionally permitted types of use of land plots and capital construction facilities on the territory of this zone, established in Appendix 3 to the Law of St. Petersburg "On the Rules for Land Use and Development of St. Petersburg" dated February 16, 2009 No. II) are presented in the following table:

Table 4.1 - Types of permitted use of the research object

Objects of the types of use marked in paragraph 3 of this article with the sign (*) can only be located on land plots directly adjacent to the red lines of streets, roads, squares, driveways, embankments, boulevards that are public areas, with the exception of intra-quarter driveways, in the absence of legislation prohibiting their placement.

The minimum area of land.

It is allowed not less than the sum of the area occupied by the capital construction object existing or located on its territory, and the area of green areas required in accordance with these Rules, the area for parking spaces, driveways and other auxiliary facilities required in accordance with these Rules and technical regulations for its maintenance and operation.

The coefficient of use of the territory.

The land use factor is defined as the ratio of the maximum total area of apartments that can be placed on the territory of the land plot to the area of the land plot. The following limiting maximum values of the area utilization factor are set: - for mid-rise and high-rise residential buildings up to 9 floors - 1.7; - for plots of multi-storey residential buildings of 9 floors and above - 2.3.

Minimum indents of buildings, structures, structures from the boundaries of land plots.

Minimum indents from the boundaries of land plots of walls of buildings, structures, structures without windows: at a distance that provides standard insolation and illumination at a height of 6 meters or more at any point, along the borders of adjacent and separated territories of common use of land plots or along the borders of territories where land plots are not formed; in case of adjoining territories (land plots) located within the boundaries of territorial zones, the urban planning regulations of which do not establish the types of permitted use, for which it is necessary to provide standard insolation and illumination, a minimum indent from the boundaries of the plots that do not coincide with the red lines is allowed, 0 meters.

Minimum indents from the boundaries of land plots of walls of buildings, structures, structures with windows: at a distance that provides standard insolation and illumination at a height of 6 meters or more at any point, along the boundaries of adjacent land plots, along the boundaries of land plots separated by common areas, or along the boundaries of territories on which land plots have not been formed, but not less than 10 meters;

In the case of adjoining territories (land plots) located within the boundaries of territorial zones, the urban planning regulations of which do not establish the types of permitted use for which it is necessary to provide standard insolation and illumination, a minimum distance of 3 meters from the boundaries of the plots that do not coincide with the red lines is allowed.

The minimum indents from the boundaries of the land plots of the walls of buildings, structures, structures along the boundaries of the land plots coinciding with the red lines of streets and driveways are established: for residential buildings with apartments on the first floors and educational and educational institutions facing the main streets - 6 meters; for residential buildings with apartments on the first floors and educational and upbringing institutions facing other streets and public driveways - 3 meters; for other buildings - 0 meters.

Maximum protrusions beyond the red line of parts of buildings, structures of structures.

In accordance with Article 7 of Part II of these Rules: allowed: in relation to balconies, bay windows, canopies - no more than 3 meters and above 3.5 meters from ground level.

The maximum height of buildings, structures, structures on the territory of land plots.

The maximum height of buildings, structures, structures on the territory of the land plot located in built-up areas is not more than 30% higher than the average height of existing buildings in the quarter, namely 30 meters in the development of built-up areas - is not established), unless a different value is indicated on the diagram of the limits of action of urban planning regulations in terms of the maximum height of buildings, structures and structures. At the same time, if the restrictions related to the same territory coincide, the minimum limit parameters apply, with the exception of cases where local dominants are placed.

The minimum share of green areas.

Table 4-2. The minimum share of green area for sites with different types of use.

Type of use	Use code	Minimum area of green areas
Multi-family residential buildings		23 square meters per 100 sq. meters of the total area of apartments in the capital construction project on the site
Gardens, squares, boulevards		95% of the territory of the land plot with a plot area of less than 1 ha; 90% - with an area of 1 to 5 hectares; 85% - with an area of 5 to 20 hectares; 80% - with an area of more than 20 hectares
Complexes of attractions, amusement parks, water parks		0% of the territory of the land plot with the area of the land plot less than 1 ha; 10% - with an area of 1 to 5 hectares; 20% - with an area of 5 to 20 hectares; 30% - with an area over 20 hectares
Hospitals, health resorts, social welfare facilities, facilities for recreational purposes, green spaces that perform special functions.	10910;10940; 10950; 12600; 12510	60% of the land area
Dosh objects, early and the average overall image. (schools)		50% of the land area
Individual residential houses, dachas, objects of secondary and higher professional education; objects of physical culture and sports, including sports clubs; objects of ritual activity	10100; 10200; 10810; 10820; 11030; 11040; 13800; 11010; 11020	40% of the land area
Public utilities, agricultural facilities. use, transport facilities, special parks (zoos, botanical gardens)	10400, 13100, 13200, 13300, 13500, 14200, 14500, 13000 11120	not installed

When forming land plots of multi-apartment residential buildings, parts of the adjoining open green spaces required by these Rules (up to 30% of their area) can be allocated for merging into independent land plots of intra-quarter public gardens (gardens)

The minimum number of parking spaces.

The minimum number of parking spaces for storing individual vehicles on the territory of land plots - in accordance with Article 10 of Part II of the Rules: parking place for 20 beds, as well as 1 parking place for 5 employees.

Minimum number of places on loading and unloading areas

The minimum number of places on the loading and unloading areas on the territory of the land plots - in accordance with Article 11 of Part II of the Rules: is determined on the basis of: one place for objects with a total area of 100 square meters to 1500 square meters and plus one place for every additional 1500 square meters total area of facilities - for trade facilities (code 105), public catering facilities (code 106), industrial facilities (code 121), for enterprises for primary processing, packaging of agricultural products and maintenance of agricultural production (repair, warehousing) (code 131.2); one place for objects with a total area of 100 square meters to 1250 square meters and plus one place for every additional 1250 square meters of the total area of objects - for warehouse objects (code 122).

Minimum storage space

1. The minimum number of places on the loading and unloading areas on the territory of the land plots is determined on the basis of: one place for objects with a total area of 100 square meters to 1500 square meters and plus one place for every additional 1500 square meters of the total area of objects - for trade objects ( code 105), public catering facilities (code 106), industrial facilities (code 121), for enterprises for primary processing, packaging of agricultural products and maintenance of agricultural production (repair, storage) (code 131.2); one place for objects with a total area of 100 square meters to 1250 square meters and plus one place for every additional 1250 square meters of total area of objects for warehouse objects (code 122).

2. The area of parking spaces for storage (technological sludge) of trucks is determined at the rate of 95 square meters per vehicle (including travel); when parking areas adjoin the carriageway of streets and driveways and the longitudinal arrangement of cars - 70 square meters per car.

Maximum height of fences for land plots of residential development

The maximum height of fences for land plots of residential development - in accordance with Article 13 of Part II of these Rules: along express highways - 2.5 meters; along streets and driveways - 1.8 meters; between adjacent building plots - 1.8 meters without agreement with adjacent land users. More than 1.8 meters - in agreement with adjacent land users. For residential areas, a height of 1.8 meters may be exceeded, provided that this does not violate the volumetric and spatial characteristics of the surrounding buildings and landscape, insolation standards and natural light.

Maximum hazard class

The maximum hazard class (according to the sanitary classification) of capital construction objects located on the territory of the zone is V (with the exception of bus stations and intracity transport facilities). The rules for land use and development of St. Petersburg distinguish more than 100 types of permitted use of land plots. However, real estate market professionals name significantly fewer segments of the land market. The characteristics of the plots, which cause their other difference, are recognized as pricing factors that affect the price of an object within a similar group, segment.

The segments allocated by the market by functional purpose include land plots intended for use under:

Implementation of low-class summer cottages and horticulture;

Residential low-rise buildings (townhouses and cottages);

Residential high-rise buildings;

hotel development;

Production and warehouse function;

parking lots;

Open parking and parking lots;

Sports facilities;

Since we are talking about market segmentation, the land plots intended for development with socially oriented objects and communal facilities belong to the group of investment-unattractive objects. For the purposes of analyzing the best and most efficient use of a property by a typical investor, further segmentation of this group is meaningless.

The rules for land use and development of St. Petersburg also indicate options for the use of land plots that are limited in circulation or completely withdrawn from circulation. When choosing the option of the best and most efficient use of a property by a typical investor, such land plots are not analyzed. The types of functional use of the studied land plot presented in the rules of land use and development of St. Petersburg can be grouped as follows:

Table 4-3 - Types of permitted functional use of the studied land plot

	Resolution option. use, specified in the rules of land use and development of St. Petersburg	Market segments com. real estate
	To accommodate catering facilities	Trade
	To accommodate consumer services (including baths)	Objects of preschool, primary and secondary general education (schools)
	For placement of objects of secondary and higher professional education
	To accommodate outpatient clinics
	To accommodate social security facilities ...

Consideration of risks when choosing the option of the best and most efficient use and evaluation of the object

Let us also pay attention to the fact that the classical market price" - This value in exchange, which is equal to the price that can be paid with a high probability in a transaction modeled by the appraiser between the seller and the buyer. When modeling the behavior of these typical market entities, the appraiser relies on completed transactions with analogous objects, which are classified as random events with prices as random variables. By modeling a transaction and determining the market value as a hypothetical price for a probable transaction, the appraiser does not guarantee the customer that the transaction with the object will occur at a price exactly equal to the market value. The appraiser can determine and inform the customer only expected value the price of a hypothetical transaction and the confidence interval for this value, indicating the corresponding confidence level (this should be clearly stated in the regulatory documents governing valuation activities). It follows that the required algorithms for selecting the NNEI option and assessment procedures should be based on known methods of risk analysis.

The content of the principle of the best and most effective use and the rule of its application

The proposed new edition of FSO No. 2 describes in sufficient detail the very principle of NNEI and formulates a rule for its application in assessing all types of objects of civil rights:

“2.4.4. The principle of the best and most efficient use of an object takes into account that when analyzing the value of an object, a typical user considers the possibility of ensuring the most productive use of this object by choosing from the list of potentially useful functions that function (or that set of functions) that is legally permitted, physically realizable, economically feasible and financially feasible. At the same time, the functional use is considered to be the best, which provides the most complete (in accordance with consumer standards and social norms) satisfaction of the needs of users of this resource. Forming a qualitative criterion for choosing the (best) functional purpose of an object, this part of the principle should be taken into account for any purpose of the object, including when using an object that does not involve generating income. The most efficient is the use at which it is possible to achieve the maximum productivity of the object. This part of the principle forms a quantitative criterion for choosing a function that ensures the achievement of the specified level of profitability of the object.

It should be borne in mind that the implementation of the principle of the best and most efficient use (NNEI) of an object of civil rights is mandatory when determining the market value of real estate, business, large vehicles. The use of a valued object of civil rights, in which this object has the highest value and which meets the above requirements, is recognized as the best and most effective.

Thus, according to the NNEI principle, it is necessary to conduct a comparative analysis of functions from the full list of functions that are potentially useful for holders of an object of civil rights. At the same time, only those functions for which there is market demand should be included in the specified list. The presence and parameters of demand must be confirmed by the appraiser with data obtained in the process of researching the market for objects similar to the object of appraisal. It is envisaged that in the event of a difference between the NNEI option established by the analysis and the current use, the transformation of the object until it reaches the NNEI parameters will be carried out by the future owner, to whom the object will pass after the simulated transaction.

The new draft provides a brief description of the selection process for the NNEI option: “4.4. Choice of the option of the best and most efficient use of the object of assessment. Based on the results of information processing, an analysis is carried out in order to select the option of the best (socially acceptable) and most effective (maximum productive) use of the object of assessment. This analysis is carried out through the sequential implementation of five stages:

an exhaustively complete list of possible (potentially useful) options for the use and development of the object of assessment is established;
the specified list excludes options, the implementation of which will be impossible due to insurmountable legal prohibitions and social burdens;
further, options are excluded from the remaining list, the implementation of which is impossible due to physical limitations;
from the list of legally permitted and physically feasible options, economically inexpedient (not providing a return on capital and a minimum acceptable return on capital) and financially unfeasible (not secured by the possibility of using the phenomenon of financial leverage - obtaining loans on acceptable terms) are excluded;
the remaining options are compared with each other in order to select from them the option that is most productive, that is, having the highest value of the net present value of future income at the lowest level of riskiness (with a smaller confidence interval under risk or with the lowest level of possible losses under uncertainty).

When valuing assets, the possibility of changing the functional purpose of the object of assessment or its parts varies, including without changing or with changing the characteristics of the object. When evaluating a business, the possibilities of diversifying the product of production, factors of production and business structure are analyzed. The choice of the most productive option for using an object is carried out taking into account the principles of balance, economic separation, economic size, increasing and decreasing returns, and others. The choice of options for using the object of assessment is carried out taking into account the risks.

Note that here instead of the widely used phrase "analysis of the best and most effective use ...", which appeared after the "literal" translation of the American "highest and best use analysis", the phrase "analysis for the purpose of choosing an option ..." is written, but it can be written in a simpler way - “selection of the option for the best and most efficient use of the object of assessment” (various options are analyzed, from which the best and most efficient are selected).

The description of the analysis algorithm in order to select the NNEI option should be presented in the relevant standards (in large blocks) and in the Guidelines (with an exhaustively complete description of all the details - specific for each type of objects of assessment). Next, we will discuss some of the problems of forming such an algorithm - first for real estate (“which gave rise to” the problem of applying the NNEI principle in valuation), then for movable property and business.

Fundamentals of analysis to select the best and most efficient use for real estate

Preparing the basis for determining the market value of a land plot that is free or, as it were, free from improvements (as part of a real estate object), the appraiser selects the NNEI option based on an analysis of possible, legally acceptable and potentially demanded by the market (including those proposed by the customer of the appraisal) options for its use with taking into account the principles:

balance (a set and set of functions are harmonized with the needs of society);
economic division (the dependence of the efficiency of the use of the site is studied in the spatial and temporal division of this use);
economic size (it is possible to increase the cost of each site when connecting several sites in or increase the cost of the assessed site when joining a neighboring site to it - within the framework of one NNEI project);
increasing and decreasing returns (the dependence of the cost of a land plot on the height of a building has a maximum - its own for each function);
competition (risk analysis should take into account the possibility of planning by the owners of several neighboring plots of land to implement the same functions).

The set of functions considered for implementation on a land plot (free or, as it were, free) is relatively small: office, retail, hotel, residential, industrial, warehouse (sometimes paired combinations of these functions). The parameters of buildings for each function vary in accordance with the specified principles, market preferences and urban planning restrictions. At the same time, an analysis for a land plot, as it were, is mandatory, regardless of the real possibility or expediency of demolishing improvements: in the cost approach to assessing a single object, the market value of a land plot is determined in the NNEI version for a seemingly free plot, and the difference between the values of the value of this plot in the NNEI variant and in current use is considered as external obsolescence of improvements, the parameters of which do not fully correspond to modern market preferences (up to the negative cost of improvements; see). This latter is important to keep in mind when developing a facility management program, when planning the modernization of improvements, and when regulating relations in case the land and improvements have different owners.

When choosing the NNEI option for a site with existing improvements, the number of features potentially useful for use on the site is greater than when analyzing land use options. The latter is explained by the fact that when choosing the NSEI version of a single object, numerous combinations of functions are considered in different rooms of the existing building, as well as in potentially useful and planned extensions and superstructures (here, most often, one has to consider the finished building as an object of a “universal” profile). Note that when forming a sample of potentially useful functions for each object, the appraiser should rely on the results of market research, confirming the demand for renting the appraised object for each of the functions included in the list. For example, we point out that when compiling the list of functions presented in table 5.5 of the monograph, its compilers (certified graduates of the training program for real estate managers) had to give examples of renting out premises for these functions.

As is known, the choice of the NNEI option from the analysis of the complete set of functions compiled at the first stage, first for the land plot, and then for the plot with improvements, is carried out in the next four stages.

At the second stage of the analysis, functions that have legal contraindications of three levels are distinguished from the specified set:

prohibited by laws or by-laws based on laws, including town planning regulations approved by local legislative bodies (hereinafter such functions are excluded from consideration);
contrary to the orders of executive authorities that are not based on laws (in relation to these functions, the possibility of overcoming prohibitions is being explored: with an economic justification for the preference of a new option for using land and improvements - for the executive power of the settlement and with an assessment of additional costs - for the owner of the object of assessment);
potentially capable of causing public resistance (the possibility of overcoming protests with an assessment of the costs of producing "compensatory" benefits for the "protesting" population is being studied).

The possibility of overcoming prohibitions and protests is studied with the participation of the customer’s lawyers or consultants and in most cases is successfully predicted - with an assessment of the likelihood of a positive decision within a reasonable time and with a forecast of the amount of additional costs (all taking into account the risks and, of course, with the support of these actions by a reasonable customer of the evaluation interested in determining the maximum value of his property).

At the next (third) stage of the analysis, functions are selected from the remaining list, the implementation of which may be difficult due to the limited capabilities of the site and improvements (small size of the site, there are problems of a geological nature or uneven terrain, small sizes of premises, limited opportunities to provide the facility with resources and etc.). Functions are excluded from further consideration, the implementation of which will be impossible due to insurmountable difficulties in eliminating these restrictions. However, the list for analysis remains functions (taking into account risks), the implementation of which is possible at the expense of additional costs. In particular, the size of the land plot can be increased by acquiring the missing part of the area from a neighbor, uneven terrain can be corrected by attracting specialized contractors, the problem of providing resources can be solved if the future owner of the appraised object participates in the creation of new elements of the production and delivery infrastructure resources.

At the penultimate (fourth) stage of the analysis, those of the remaining functions are excluded, the implementation of which cannot provide a full return on invested capital and return on capital even with a rate equal to the risk-free rate Y rf. From the previously truncated list of functions, only those functions are left for further analysis, the implementation of which turns out to be economically feasible, which corresponds to the condition NPV> 0 at a rate of return equal to Y rf. Note that the functions left for further analysis with a low rate of return on capital may turn out to be potentially in demand when harmonizing the set of functions proposed (with maximum productivity achieved) for implementation at the facility with existing improvements.

At this stage, the financial feasibility of the remaining functions is additionally checked: from the list of the latter, functions are excluded for the implementation of which it will not be possible to obtain borrowed funds on acceptable terms (the phenomenon of positive financial leverage sets up the acquisition or creation of a real estate object only with the involvement of borrowed funds - at the interest rate on the loan less than the general rate of return on capital).

Finally, at the fifth stage of the analysis, from a significantly reduced list, a function (or combination of functions) is left, the implementation of which (minus all the additional costs mentioned) provides the highest profitability of the project and the maximum cost of the object - with an acceptable level of reliability of the predicted result. The latter means that in the final choice of the NNEI option, the current value of future income should be calculated taking into account risks, not only in the rates of return on capital (its own for each function), but also in project development scenarios, the features of which are not taken into account by risk premiums in the structure of discount rates. (risks associated with overcoming bans and protests, the implementation of projects to eliminate the physical defects of the facility, ensuring the reliability of funding sources, and others). Final decision on the choice of the NNEI option justified and accepted by the appraiser. At the same time, it is assumed that, in accordance with the assessment task, the option is selected that corresponds to the highest possible value of the object of assessment, in which a reasonable customer should be interested, who wants to receive an opinion on marketcost. If the customer for some reason does not like the use case justified by the appraiser, he can change the order and ask instead of the market value to determine market value in current use or investment value(in case of choosing an option that is different from the current use, but also not NNEI). The appraiser needs to keep in mind that it will be the buyer of the hypothetical transaction (value in exchange is determined!) It follows from this that the objections of the customer of the appraisal (as a rule, the seller of the property) are unlikely and can arise only if there are difficulties in the implementation of the transaction due to the inconsistency of the selected option with the expectations of a typical buyer (due to shortcomings in the appraiser's argumentation when choosing the NNEI option).

In connection with the foregoing, we add (for more details see in ) that the appraiser prepares a conclusion on the choice of the NNEI option using the decision criteria: for conditions of uncertainty (taking into account hazard indicators in the absence of information about the probabilities of scenarios) and for risk conditions (taking into account importance indicators, if it is possible to estimate the probabilities of the scenarios). In the simplest version of the analysis, in order to select the NNEI option, optimistic, probable and pessimistic scenarios for the development of the project are considered, with an expert assessment of the probabilities of these scenarios, determining the expected NPV value and the confidence interval (standard deviation) for it. The option for which the NPV value is maximum at the minimum (or comparable with other options) confidence interval (confidence interval, standard deviation) is selected as the NNEI.

In the absence of possibilities for assessing the probabilities of these scenarios, the choice of an option is carried out using the Wald and Savage criteria (see ) or simulation methods - now based only on optimistic and pessimistic scenarios (see ). At the same time, the appraiser must inform the customer that the market value of the property is determined as the expected price of the transaction with the confidence interval and confidence level presented in the report.

It should be noted that, as follows from the practice of real estate valuation, in the case of valuation for the purposes of sale, appraisers-consultants, along with a real estate valuation report, can offer the customer (to his satisfaction) useful recommendations on the strategy and tactics of the transaction based on the results of choosing the NNEI option (formation such recommendations should not be governed by valuation standards).

Features of choosing the option of the best and most efficient use for movable property

An analysis of the practice of valuation of movable property indicates that in most cases the designed and implemented use of movable property is the most effective, but it cannot be excluded from consideration of situations in which typical participants in the transaction can gain additional benefits from choosing the NNER option on market grounds.

First of all, let's pay attention to the fact that the market value is economiccost id, which manifests itself (by definition) only when supply is limited and in the presence of solvent demand. The market for mass-produced and consumer goods can reach perfection, in which the price regulation mechanism ensures the achievement of a weakly changing (almost static) equilibrium supply and demand. In such a state of the market, an approximate equality of the market value of the appraisal objects with the equilibrium price of similar objects is achieved.

However, as the valuation objects that act as goods on the market become more complex, their mass production decreases, the set and duration of preparatory procedures become more complicated until the moment of the transaction, the parameters of the market for such goods are increasingly different from the parameters of a perfect market - with the replacement of the phenomenon static» equilibrium regime " dynamic» equilibrium. At the same time, transactions are also made with arbitrarily complex objects (ships, real estate), under the action of the price mechanism for regulating the behavior of the participants in the transaction, but now the market value turns out to be equal to the “quasi-equilibrium price”, which cannot be determined by constructing supply and demand curves, but it is possible establish by methods of comparative analysis of transaction prices (see). At the same time, for movable property, which is less complex in comparison with real estate, the task of choosing the NNEI option is also significantly simplified: for relatively simple objects (machine tools and cars), only the preferences of the subjects of demand, configuration options, methods of financing the transaction are analyzed, while for complex objects (sea, river and aircraft) and functions may vary. In particular, machine tools can be purchased by enterprises of different profiles and different workloads of production factors. If one part of typical enterprises uses machines (with special equipment) to produce a labor-intensive and highly liquid product in three shifts, and another part of enterprises (also not small) uses the same machines with simpler equipment to produce products that are easier to manufacture and work in one or in two shifts, then the enterprises of the first group, with a limited supply of machine tools on the market, are ready to pay more for each machine than the enterprises of the second group.

The appraiser, invited to determine the market value of a particular machine, studies the demand for such machines, determines the value of the appraisal object using the income approach, based on data on the part of income generated by such a machine in the production process of the enterprise, obtains different values for the machines used by these two enterprise groups. If both groups of enterprises have demand for this type of machine, then with a limited number of machines to be produced, the appraiser chooses the high-efficiency method of use (with a labor-intensive business product with three shifts) as the NNEI option.

It should also be borne in mind that if, in typical practice, such machines are purchased by enterprises using credit resources, then the valuer should take into account the possibility of enterprises choosing to lease or purchase - with a preference for the option in which the machine will cost the enterprise less. Thus, the appraiser should additionally take into account the possibility of participation in the competition for the acquisition of the machine and the leasing company, analyzing the income that the machine can bring to the business of such a company.

notice, that small circulation And very expensive passenger cars are sold not only to private owners, but also to rental and leasing companies, which, in conditions of limited supply, are able to pay more than a private person. This should be taken into account by an appraiser who was invited to determine the market value of a car from the first batch of exclusive samples that arrived at the dealership, or the value of a relatively rare car that appeared in a private owner. At the same time, options should be considered for offering a car for sale both in a standard configuration and in a package with a series of additional elements, the inclusion of which in the transaction package can bring additional benefits to the seller (according to the principle of contribution: the increment in the value of the package may be greater than the sum of the costs of the elements included in it ). On the recommendation of the appraiser, who takes into account the peculiarities of the preferences of different types of buyers, the dealer prepares his price list for the entire set of models and configuration options, and the private customer of the appraisal prepares his options for the offer price.

A useful example is the choice of the best (without a quantitative justification of the “most efficient”) option for using a car, taking into account the demand for its equipment. This refers to an example with an assessment for the purposes of selling a used car of a "short-circulation" model "Niva-Bronto" (an extended version of the three-door "Niva" - more convenient and more reliable in comparison with the base model), handed over by the owner to the dealer in exchange for a new car of a different model . The dealer's appraiser found out that there are offers for the sale of used cars of this model, and new cars are in demand (selling on a "short" record at the dealer in VAZ). Further, the appraiser drew attention to the fact that the object of appraisal has branded wheels with all-season tires that are not provided for by the standard assembly, a “kenguryatnik” with fog lights, a convenient non-standard trunk, and modern equipment. The appraiser found out how much the price of a new analogue of the car being appraised would increase for its buyer (at the date of valuation) after installing the specified additional elements, determined the loss of value due to wear and tear for the entire car (with the mentioned additional elements) and investigated the demand. His survey of a sample of potential buyers from the gardening community showed that they welcome the new model, but only the installation of the trunk is considered acceptable and worthy of an extra charge, while the additions to the standard equipment of the rest of the elements qualify as “over-improvements” that are not worth paying for. At the same time, the club of hunters and fishermen reacted positively to all these additions, with a reserved attitude towards the potential proposals voiced by the appraiser for the additional installation of a power steering and navigator on the car (also not provided for by the standard assembly). Taking into account supply and demand, the appraiser determined the market value of the car. After explaining the appraiser and comparing his version with the options of his earlier attempts to sell the car, the owner agreed with the result of the appraisal, the car was put up for sale and about three weeks later it was sold at a price equal to the specified market value. Based on this experience, the appraiser confirmed the need for a detailed analysis of the demand for similar objects of the appraised object and recommended that the dealer offer new and used SUVs of this brand in the specified configuration.

Let's pay attention to the fact that A. Damodaran introduced the concept of "bad investments", which at the enterprise bring income that does not meet the expectations of return on the funds invested in them. He suggests considering different options for deciding the fate of such fixed assets, including options for refusing preventive repairs if the benefit from stopping repairs exceeds the losses from reducing the economic life of the object. We are familiar with situations in which, in response to the questions of the appraisers, representatives of the customers of the appraisal reported on the planned upgrades of existing production lines (with the replacement of tooling or individual elements of equipment) in order to launch the production of a new, more promising product. The latter situations should be considered when determining the market value of a business (including surplus and non-core assets) - in the NNEI version of these assets (with the identification of functional and external obsolescence of some of them).

Concluding the discussion of the features of the analysis in order to select the NSEI option for movable property, let us pay attention to the fact that much more options for choosing such options (in comparison with machines and cars) are revealed when evaluating river, sea and aircraft. Here, not only options for completing and financing transactions can be analyzed, the sets of implemented functions are also subject to research, taking into account legal restrictions on these options in connection with the norm of the law on state registration of ships and transactions with them.

Opportunities and challenges of choosing the best and most efficient use option in business valuation

When determining market value of the business the algorithm for selecting the NNEI option is implemented in full if the controlling (and 100%) stake is evaluated (with a focus on the preferences of the market and potential buyers), and partially when assessing a minority stake (only the intentions of the board of directors and company management are taken into account, including the appraiser's proposals accepted by them).

Let us pay attention to the assumptions of opponents that the choice of the NNEI option for business should be only when determining the investment value. These assumptions contradict the following theory: for any object, valuation without application of the NEUT principle gives a value in current use, which turns out to be equal to the market value only if the current use is NEUT. When determining the investment value, the NNEI principle is considered only as a recommended one and is applied only in agreement with the initiator of "atypical (investment) motives" - the buyer or seller.

Let us note the potentially positive consequences encountered in the practice of business valuation:

diversification of business products and sales markets(the possibilities of planning and organizing the production of new types or improving the parameters of manufactured goods and services are considered, the possibilities of entering new territorial and product segments of the markets are analyzed - all taking into account the need to introduce organizational and technological innovations);
factor development(the consequences of introducing new promising technologies, creating new infrastructure elements, upgrading equipment, restructuring and developing personnel are analyzed - all within the framework of procedures for determining the market value of assets in the NNEI version when implementing a cost approach to business valuation);
business restructuring(the prospects for introducing organizational changes in the business management system, the possibility of mergers, acquisitions, separation of companies, the formation of a holding, the transformation of divisions into independent enterprises, the creation of branches and subsidiaries are considered).

For example, we indicate the changes that turned out to be significant for the results of business valuation (with a very noticeable increase in the value of the property being valued):

changes in the product range of a bakery plant (with minor improvements in equipment equipment), a brick factory (with a redistribution of production capacity in favor of a type of product popular on the local market), a woodworking enterprise (with the complication of a product under conditions projected increase in the shortage of raw materials);
compaction of production units of a small enterprise proposed by the appraiser and accepted by management, with the allocation of premises for rent (in order to obtain additional income);
the release of part (more than 30 percent of 500,000 square meters) of premises for leasing implemented by the management of a large enterprise (as a result of the introduction of “internal leasing”, self-supporting divisions have optimized their needs for premises);
a change in the staffing table of a small enterprise proposed by the appraiser and accepted by management (the appraiser was helped by the experience of a more “advanced” company of a similar size, studied in the process of implementing a comparative approach to the valuation of this enterprise);
the construction of a new warehouse building as part of the logistics complex planned by management and accounted for by the appraiser (the contribution of the free part of the land plot to the value of the business has increased);
the appraiser's proposal accepted by the company's management to replace the option of selling the excess part of the property (a plot of land with three buildings) with the option of transferring this property to trust management, with the reconstruction of improvements for a new purpose and preserving the possibility of a profitable sale of this appraisal object in the future;
the appraiser's proposed comparison of options for technical re-equipment of the enterprise using borrowed funds or leasing and the appraiser's recommendation accepted by the customer on the preference for choosing a leasing scheme;
the division of a large enterprise into two: one became the owner of fixed assets, that is, the “household”, the second remained a “firm” with the same production team, the same system of orders and sales of products, but now renting fixed assets from the “household” (a significant increase in the total value of the business after the division, it is ensured by attracting tenants of unloaded premises and expensive equipment from among the potential competitors of the “company”).

There are also more complex situations, similar to the examples given by forum participants. So, for example, when discussing (several years ago) an order for a business valuation of a moderately successful enterprise, we drew the customer's attention to plans announced by the city to change the functional purpose of the territory to which the land leased by this enterprise belongs. As part of the campaign to move industrial enterprises from a prestigious location to industrial zones, the city offered to provide these enterprises with land, infrastructure, resources, and, importantly, the enterprise retained the right to lease “prestigious” land if it agreed to participate in an investment project to create tourism infrastructure. We proposed to the management to evaluate the business with the development of a program for the relocation of the enterprise, with the introduction of the right to conclude a lease agreement for a land plot in a prestigious area and ownership of the improvements of the enterprise to be reconstructed as a contribution to the authorized capital of a new tourism business enterprise. The customers did not agree to this proposal, and the order did not take place, since it did not make sense to evaluate the business as of the date of negotiations without taking into account the immediate prospects (today, the previously predicted prospect of re-profiling the territory was realized to the detriment of the business of the enterprise, the assessment of which did not take place).

Note that the choice of the NNEI option leads to convergence of the results of business valuation using income and cost approaches. There has never been a time when a reasonable customer was dissatisfied with the results of an assessment based on the choice of the NNEI option. Moreover, we note the growing interest of such customers in the possibility of obtaining the maximum value of the market value provided by the specified choice of the NNEI option. The presence of such interest was already announced several years ago in a speech at a conference of the Russian Society of Appraisers by a representative of Lukoil. He expressed regret about the lack of practice of appraisers varying the business plans and business structure of the enterprise being assessed in order to justify the NNEI option (in response to a remark from the presidium, he said that the appraiser was ready to pay quite a lot of money for a report with the mentioned variations). We supported this statement, drawing attention to the fact that in the process of these variations, the appraiser, of course, takes into account all the proposals, projects, expectations and advice from the management of the enterprise, and later convinces with numbers of the advantage of the option recommended by him, if such an advantage is found.

In conclusion, we note that the problems of choosing the NNEI option for assets and business described in the article and the examples given are taken from real practice. It is far from always that appraisers are smarter than managers of enterprises being appraised and owners of assets (you have to return for revision reports that did not even take into account what managers or owners planned), but recently appraisers are increasingly initiating a search for options and achieving positive results - with complicity customer and to his satisfaction. In the context of the ongoing crisis with the expected prospect of a way out of it, which is possible only in the case of innovative development of the economy, the need to choose NNEI in business valuation manifests itself almost everywhere (to a greater or lesser extent). This trend is irreversible and in the near future appraisers will need to search (together with the management and specialists of the enterprises being valued) for radical transformations at the object of appraisal - up to changing the business based on existing assets. Under these conditions, it becomes obvious that it is necessary to develop in detail and reflect in the normative documents of the National Council for Valuation Activities all aspects of the problem of analysis in order to select the NNEI option when determining market value any object of civil circulation. In the transitional period required for the development of new versions of regulatory documents and the development of the analysis methodology by the community of appraisers, it is proposed to introduce the concept of " market value in current use” (without choosing the NNEI option), indicating the list of cases in which it is sufficient to determine this cost instead of market value, the establishment of which is provided for by modern regulatory documents.

The owners of the patent RU 2543315:

The invention relates to computer technology, can be implemented on modern high-speed computers and used, for example, in the selection of effective options in search, recommender systems, decision support systems, Internet networks, systems for automatic classification of data packets, and in other related areas. The implementation of the claimed invention may include storing information on physical media, magnetic disks, network storages of information, processing it on a computer and providing the resulting set of effective options to the end user in any form available to him.

Before presenting the invention, for convenience and unambiguous understanding, it is advisable to provide decoding and definitions of the symbols and/or terms used below.

A search engine is a computer program designed to search for information on the Internet. The search is performed on the basis of an arbitrary text query formed by the user. The search results are presented to the user sorted according to a certain characteristic of relevance to the query. Examples of search engines are Bing, Google, Yahoo, Yandex.

Recommender system - a computer program that selects from the entire set of presented alternatives (options) those that may be most interesting to a particular user, based on a number of characteristics, for example, a query entered by the user in a search engine. It should be noted that in most cases, recommender systems present the result either as a set of recommended options, or as a ranking of all or part of the presented options. Thus, the ways of processing and transforming information within the framework of recommender systems work in related areas, such as, for example, the task of assessing the effectiveness of enterprises, etc.

The principle of superposition (in the context under consideration, in contrast to the well-known principle of superposition in physics) consists in the successive exclusion of variants from the initial set using procedures that may be different at each stage of exclusion. An example of procedures is given in Appendix 1. At the first stage, the elimination is made from the entire initial set of options, at the second stage, the input set is the effective options identified at the first stage, and so on.

Effective ("good") elements (options) are those elements that are the best, most preferred, most useful according to the given parameters for solving specific problems in which it is necessary to rank the options, and to meet the information needs of users (people, specialists, agents). ).

Inefficient ("bad") elements (options) are those elements that obviously never (under no circumstances) can be used to solve specific problems, since there are more preferable options for their solution.

The value of efficiency, with the help of which the rules for selecting and ranking options are built, is set by an expert.

Most search engines have data storage and processing facilities that contain such performance (relevance) scores for large representative sets of queries and search results for these queries. In such tools, the query and its search results (options) are represented by their own sets of criteria and the relevance score of the search results, set by the experts.

There are various formal criteria for assessing the relevance of a search element to a search query, set constructively (such as the frequency of a word in the text or the TF-IDF criterion, which is the frequency of the use of query words in the text, taking into account the degree of importance of each word). Note that such formal criteria are rather algorithms by which existing search engines actually search, than independent criteria that evaluate the results of this search. The scores calculated by such formal criteria can still be very different from the relevance scores given by the experts.

At the moment, there are three main ways in which the selection and ranking of options takes place.

A known method for selecting and ranking options is that each option is assigned an absolute score of the degree of "importance" using the values of several criteria. The most common way is to build a regression.

In addition, the McRank classification method can be used to rank options, the essence of which is to calculate for each "request-document" pair the so-called "expected relevance" as a function of the probabilities of belonging to relevance classes obtained as a result of classification. As a result of the calculation of "expected relevance", the ranking of the query-document pair within each query is in descending order of "expected relevance" (L.Ping, K.J.S. Burges, K.By - McRank: Learning to Rank Using Multivariate Analysis and gradient enumeration acceleration, NIPS Curran Associates 2007 - ).

A known method of choosing alternatives, which consists in pairwise comparison of two options in order to identify the best of them. Based on the formation of such relations, the order is built, with the help of which the choice of options takes place.

An example of a well-known method is the support vector machine, which consists in translating the original vectors into a higher-dimensional space and searching for separating hyperplanes with a maximum gap in this space (K. Cortes, Vapnik V.N., Support Vector Machine, Machine Learning Magazine, 20, 1995 - [C.Cortes, Vapnik V.N.; "Support-Vector Networks", Machine Learning, 20, 1995]), as well as other methods such as:

RankNet (Microsoft Bing search engine, C.J.S. Burges, T. Shaked et al. "Learning to Rank Using Gradient Descent", ISML, 2005: 89-96 - ), the essence of which is to use a "neural network" and probabilistic cost function for ranking search results,

RankBoost (J. Freund, R. Yer, R. E. Chapae and J. Singer. Efficient brute force algorithm for combined preferences, Machine Learning Research, 4:933-969, 2003 - ), which is based on the procedure sequential construction of a composition of machine learning algorithms for classifying pairs of documents.

FRank (M.Tsai, T.-Y.Liu, et al. Frank: A Ranking Method with Fidelity, CIGIR 2007) Loss, SIGIR 2007]), which is a modification of the RankNet method, but instead of entropy values, the distribution accuracy function is used as the cost function, and others.

There is a method for choosing alternatives, which consists in a list comparison of options. In this case, the filtering of the entire set of alternatives is performed according to the specified rules.

Examples of this method are:

1. A method for constructing trees, minimizing the ListNet penalty function, in which a probability space is introduced on the set of permutations. The entropy function on the introduced space is used as a loss function. (Zhe Cao, Tao Kin, Tai-Yan Liu, Ming-Feng Tsai and Hang Li. Learning to Rank: From Pairwise to List Approach, 2007 - ),

2. The method of list comparison of variants RankCosine, which uses a loss function based on the similarity of the cosine of the angle between the ranked list and the original list of the training set, to rank the search results (T.Kin, H.-D.Zhang, M.-F.Tsai, D.-S. Wang, T.-Y. Lew, X. Lee: Query-Dependent Loss Functions for Information Retrieval Inf. Process. Manage 44(2): 838-855, 2008 - [T. Qin, X.-D.Zhang, M.-F.Tsai, D.-S.Wang, T.-Y.Liu, H.Li: Query-level loss functions for information retrieval.Inf.Process.Manage.44 (2): 838-855, 2008)],

3. The AdaRank ranking method, in which the AdaBoost machine learning algorithm is used to build the ranking function, which builds a linear combination of classifiers to improve the performance of the ranking model. (Yu.Hu, X.Li. AdaRank: fast-tracking algorithm for information retrieval. SIGIR 2007 - ),

4. SoftRank ranking method, the essence of which is direct optimization of non-smooth ranking metrics, (Mike Taylor, John Guiver, Steven Robertson, Tom Minka. SoftRank: Optimization of non-smooth metrics, 2008 - ) and others.

All these methods show a fairly high accuracy in their highly specialized areas.

The disadvantages of the known methods of selecting options are:

The use of complex selection procedures in working with large amounts of data, which leads to a significant increase in computational complexity;

Low accuracy in the selection and ranking of options using a large number of criteria and / and in the presence of a large number of options.

As a rule, on large amounts of data, the method of searching through decision trees is used. It consists in constructing a sequence of threshold procedures by which options are selected.

The disadvantage of the decision tree search method is the low reliability of the results, since the choice of threshold procedures as a method for selecting and ranking options is not always justified (effective). In addition, for the selection or ranking of options, not one criterion, but a whole group (their combination) can be used simultaneously, which is not taken into account in the decision tree search method. It is often impossible to select or rank the entire list of options according to one criterion (several criteria). In this regard, in order to rank options with high accuracy, it is necessary to build a large number of such trees, and the results of their work must be aggregated.

Methods are known according to RF patent No. 2435212 "Collecting data on user behavior during web search to increase search relevance", RF patent No. 2443015 "Ranging functions using a modified Bayesian query classifier with incremental update", according to RF patent No. 2367997 "Improved systems and ways of ranking documents based on structurally related information”, which consist in collecting additional information, namely in using a Bayesian classifier, collecting information about user behavior, information about the structural relationships of documents, with the help of which the selection and ranking of options is carried out. The disadvantage of the known methods is the complication of existing methods for selecting and ranking options by adding new criteria.

The closest in technical essence and the result achieved is a method for calculating the time weight for the search result, which consists in identifying a user event corresponding to the search result, and the user event has an event start time, event end time and event duration; determining the current time and determining a temporal weight for this search result based on the temporal proximity of the current time to the user event. The method assumes that the time weight changes over time, increases exponentially as the current time approaches the start time of the event, is constant over the duration of the event, peaks at a point in time over the duration of the event, and decreases exponentially as the current time moves away. from the end time of the event. The method is designed to search for information on the Internet using a temporary weight to rank the search results. (Patent of the Russian Federation No. 2435213, IPC G06F 17/30, published on November 27, 2011).

The disadvantage of the known method, as well as similar existing search technologies on the Internet, is that they usually use "rough" selection and ranking algorithms, i.e. algorithms with linear computational complexity O(n), where n is the number of options. As a rule, this complexity is achieved by simplifying (more precisely, coarsening) the developed selection and ranking rules in order to provide an acceptable level of complexity. In this case, the result achieved using such methods is of lower quality.

The technical problem to be solved by the claimed invention is to create a new method for better selection and ranking of effective options, providing high selection speed and high accuracy of the results.

The technical problem posed is solved by the fact that, according to the proposed invention, the method for selecting and ranking effective options according to the first implementation variant consists in pre-forming criteria for assessing the relevance of the option to the search query and specifying a finite number of options or a set of procedures for selecting and ranking options and the sequence of their execution for selection of options evaluated as the most effective, each of the options is evaluated according to relevance to the criteria of the search query, on the basis of which the options are ranked by assigning a rank to each of them from the condition of matching the largest number of criteria in descending order; the selection and ranking of options are sequentially carried out according to the superposition method in at least two stages, if the number of options in the remaining group of options corresponds to a predetermined final number of options for selection or all specified selection procedures have been used, the selection of options and their ranking are stopped and the options from the selected group are evaluated as the most effective, if the number of options in the remaining group of options does not correspond to a predetermined final number of options for selection, the selection of options and their ranking continue, while the selection of options, their ranking and exclusion is carried out until the specified number of options is reached or until not all specified selection procedures will be used and the selected group of options is evaluated as the most effective.

The claimed method according to the first embodiment is characterized by the following additional essential features:

At the second and subsequent stages, search query evaluation criteria are formed, on the basis of which options are ranked and options are selected from the remaining array processed at the previous stage by the superposition method using methods whose computational complexity is not lower than quadratic O(n 2) and the next group of options is excluded with a lower rank.

The technical problem posed is solved by the fact that, according to the proposed invention, the method for selecting and ranking effective options according to the second implementation variant consists in pre-forming criteria for assessing the relevance of the option to the search query and setting a finite number of options for selection, evaluated as the most effective, assessing each of options by relevance to the criteria of the search query, on the basis of which the options are ranked by assigning a rank to each of them from the condition of matching the largest number of criteria in descending order; the selection and ranking of options are sequentially carried out according to the superposition method in at least two stages, if the number of options in the remaining group of options corresponds to a predetermined final number of options for selection, the selection of options and their ranking are stopped and the options from the selected group are evaluated as the most effective, if the number options in the remaining group of options does not correspond to a predetermined finite number of options for selection, the selection of options and their ranking continue, while the selection of options, their ranking and exclusion is carried out until the specified number of options is reached, the selected group of options is evaluated as the most effective .

The inventive method according to the second embodiment is characterized by the following additional essential features:

At the first stage, options are selected in the presence of a large number of them by the superposition method using selection and ranking methods characterized by linear computational complexity O(n), and the group of options that have the lowest rank is excluded;

the method additionally specifies a set of procedures for selecting and ranking options and the sequence of their execution.

The technical problem posed is solved by the fact that, according to the proposed invention, the method for selecting and ranking effective options according to the third implementation variant consists in pre-forming criteria for assessing the relevance of a variant to a search query and setting a set of procedures for selecting and ranking options and the sequence of their execution for selecting options, evaluated as the most effective, each of the options is evaluated according to the relevance to the search query criteria, on the basis of which the options are ranked by assigning a rank to each of them from the condition of matching the largest number of criteria in descending order; the selection and ranking of options are sequentially carried out according to the superposition method, at least in two stages, the selection of options, their ranking and exclusion are carried out until all the specified selection procedures are used and the selected group of options is evaluated as the most effective.

The claimed method but the third embodiment is characterized by the following additional essential features:

At the first stage, options are selected if there are a large number of them by the superposition method using selection and ranking methods characterized by linear computational complexity O(n), and the group of options that have the lowest rank is excluded

At the second and subsequent stages, search query evaluation criteria are formed, on the basis of which options are ranked and options are selected from the remaining array processed at the previous stage using the superposition method using methods whose computational complexity is not lower than quadratic 0(n2) and exclude the next group of options with lower rank.

Additionally, a finite number of options for selection, evaluated as the most effective ones, are specified;

To select the most effective group of options, additional selection and ranking methods and the sequence of their implementation are specified, and the selection and ranking are repeated.

The technical result, the achievement of which is ensured by the implementation of the entire claimed set of essential features of the method, is to increase the speed and accuracy (reliability) of the selection of effective options in search, recommender systems due to the ability, using the principle of superposition, to regulate the complexity of procedures for identifying effective options.

The essence of the invention is illustrated in Fig.1, which shows a sequence of operations in the implementation of the proposed method, where:

1 - initial set of options (many different options);

2 - the procedure for eliminating inefficient objects at the first stage using approximate methods;

3 - a set of options remaining after the first stage of selection;

4 - cutting off inefficient variants with the help of exclusion procedures;

5 - consistent application of procedures for eliminating inefficient objects using approximate methods;

6 - a subset of options that does not contain inefficient options;

7 - the operation of ranking the group of options obtained in step 6 using both approximate and exact methods;

8 - the operation of assigning the lowest rank to all inefficient options and adding these options to the final list after the ranked options;

9 - providing the final ordered group of options to the end user;

10 - groups of ineffective variants cut off using a sequential superposition of elimination procedures.

The proposed method is based on the superposition method, which consists in the successive exclusion of previous options using certain procedures, which may be different at each stage of exclusion.

The inventive method is carried out as follows (figure 1).

There is or is being formed a large set of options 1, which may contain inefficient options.

The term "large set of options (search elements)" is considered within the concept of "Big Data" (Big Data), which appeared in connection with the development of information technology and includes approaches to processing huge amounts of heterogeneous information.

Under this concept, a large set of options (search elements) is understood as a structured or unstructured data set of huge volume and significant diversity.

In order to exclude ineffective options and select the most effective options, criteria for assessing the relevance of a variant (search element) to a search query are preliminarily formed and, if necessary, a finite number of options (search elements) are set for selection, evaluated as the most effective (as most corresponding to the criteria for evaluating relevance). search query). Next, each of the options (search elements) is evaluated according to relevance to the search query criteria, on the basis of which the options (search elements) are ranked by assigning a rank to each of them from the condition of matching the largest number of criteria in descending order. The selection and ranking of options (search elements) is carried out sequentially by the superposition method in at least two stages.

The method can be defined differently - the set of used selection and ranking methods and the sequence of their application can be specified.

At the first stage, options are selected from a large number (item 2 of figure 1) by the superposition method using selection and ranking methods characterized by linear computational complexity O(n).

For this operation, well-known methods characterized by linear computational complexity O(n) can be used, such as, for example, the rule of relative majority, the Borda rule, the over-threshold choice rule, and others. The most complete list of selection rules is given in Appendix 1.

As a result, two groups of options are formed: a group of options 10, having the lowest rank, and a group of options 3, subject to further analysis.

The group of options 10, which have the lowest rank, are excluded (item 4 of figure 1).

At the next stage, criteria for evaluating the search query are formed, on the basis of which the options are ranked. The selection of options from the remaining processed array is carried out by the superposition method (item 5 of figure 1) using methods whose computational complexity is not lower than quadratic O(n 2).

For this operation, known methods can be used, the computational complexity of which is not lower than quadratic O(n 2), such as, for example, the minimum non-dominated set, the Richelson rule, or rules based on the construction of a majority or tournament matrix (see Appendix 1).

The selection of options and their ranking is stopped and the options (search elements) from the selected group are evaluated as the most effective or promising when all used (given) selection and ranking methods have been completed or if the number of options in the remaining group of options corresponds to a predetermined finite number of options (search elements) for selection. The selection of options and their ranking can be repeated by specifying additional selection and ranking methods, as well as the sequence of their execution.

Otherwise, the selection and ranking continue to be carried out as described above (pos.7 and 8 figure 1). That is, the group of options 6 is ranked using the ranking operations 7, if necessary, you can add to it (item 8 of figure 1) options from the group of inefficient options 10. The selection of options (search elements), their ranking and exclusion is carried out (item 9 of figure .1) until the specified number of options (search elements) is reached or until all used (specified) selection and ranking methods are completed, and the selected group of options 9 (search elements) is evaluated as the most effective (promising). Thus, there is a selection and ranking of effective options, their ranking and provision of these options to the end user.

The superpositional approach is used when it is impossible to unambiguously determine by one criterion which options are effective and which are not. A distinctive feature of the method is the ability to identify, in the presence of a large number of criteria from a large number of options, those options that are effective, as well as the ability to adjust the computational complexity of the proposed method. The proposed method allows you to move from complex mechanisms for identifying effective options to composite ones, which are a combination or superposition of simpler procedures. The results of the previous stages of selection and ranking are processed at the next stages of the method.

In addition, in the proposed method for ranking options, not one criterion, but a whole group of criteria (their combination) can be used simultaneously, which is not taken into account, for example, in the well-known decision tree search method, which uses the simplest threshold procedures, the choice of which is not always justified.

Unlike known methods, the superposition method is quite flexible and allows you to vary the number of stages in the selection method.

The superpositional approach eliminates the possibility of losing efficient variants in the case of using approximate methods. After the sequential composition of the elimination stages, the remaining options are selected and ranked. All inefficient options that were excluded before the ranking procedure will have the lowest (worst) rank and will be selected (offered) for solving problems in the very last turn.

Approximate methods, which are used to reduce the number of options at a high speed, are selection and ranking rules with linear computational complexity O(n). Such rules (methods) must use (read) the parameter values of each variant (alternative) only such a number of times k, which does not depend on the number of variants (alternatives) n, and is much less than n. In the fastest (ideal) case for the rule with O(n) complexity, each option is used only once. The rule has the ability to determine whether an option is effective or not, based only on the data of this one option, without comparing it with each of the other options. For example, for the rule of discarding ineffective options, with values "below average", for some parameter (for which the values are higher, the better), it is required to calculate the value of each option only 2 times: the first time to calculate the average, and the second time to determine whether the value of this option is higher or lower than the mean. This rule refers to rules with linear computational complexity O(n).

Thus, the use of selection and ranking methods characterized by linear computational complexity O(n) provides a significant increase in the speed of selection of effective options in search and recommender systems.

However, initially it is rather difficult to use fine (exact) methods on the entire range of options due to the presence of a large number of options. When applying approximate procedures for cutting off inefficient options, the number of different options decreases, which, in the end, leads to the possibility of using more subtle methods for selecting and ranking the remaining options.

Fine (exact) methods, which are used when there are a small number of options, are understood as selection and ranking rules, the computational complexity of which depends solely on the number of times each option is used. There are rules that use pairwise "distances" between options (alternatives), in special scales. Such rules must, for each variant, enumerate all other variants, i.e. perform (n times n) operations, the computational complexity here is quadratic. There are also rules that compare each option with all possible sets of other options in order to more accurately determine the position of this option in relation to the rest. The computational complexity of such rules is even higher. It can be said that rules with complexities, starting from quadratic O(n 2), cannot be applied to the full set of options (calculated in millions) when solving the problem of searching and ranking on the Internet, and in similar problems in other fields of activity, since computational the complexity of these rules is highly dependent on the number of options available in the set.

Thus, the use of methods whose computational complexity is not lower than the quadratic O(n 2) provides a significant increase in the accuracy (reliability) of the selection of effective options in search and recommender systems.

The advantage of the method is also that it becomes possible to regulate the computational complexity of the procedure for identifying effective options. This means that if the application of certain procedures on a large amount of data required huge computing resources, then after successive exclusion of variants, the same procedures on the remaining subset can work quite quickly. In other words, by setting a certain limit on the amount of computing resources used to execute the method, it is possible to set the number of stages with which you can cut off obviously inefficient options using fast approximate methods, after which you can use rather laborious procedures that identify efficient options with enough high precision. This is the control of the computational complexity of the method.

The claimed method can also be applied in the task of learning to rank, that is, the task of choosing options with pre-known estimates of their usefulness according to the criteria. The method allows to form, according to a predetermined degree of utility (efficiency) of some options, the rules for their selection and ranking (a set of applied selection and ranking methods, as well as the sequence of their application), in accordance with which the selection and ranking of other options can be made, about the degree of utility ( efficiency) of which nothing is known.

The inventive method can be implemented using known hardware and software. The implementation of the proposed method includes:

1. Collection and storage of data /

2. Data processing, selection and ranking of options.

3. Providing results to the user.

Collection and storage of data. At this stage, the necessary information about the existing options is collected and stored. Variant information may be collected from existing data sources, such as various existing information systems, websites, web services, other data servers, computer files, ie. from all sources that store information about variants in a format suitable for further processing. Data collection can be carried out using existing software that extracts data from external sources (for example, ETL systems or tools for collecting the content of web pages on the Internet), or implemented on a computer using any programming language, in particular, a programming language C, C++, C#, Java, Python, PHP and many more. Information can be stored both on a server or a group of servers using existing platforms that store data, and on any storage medium from which it is possible to further read the available information. Also, information can be stored directly in the main memory of a computer in the case when there is no need to permanently store information.

Data processing, including, according to the claimed method, the selection and ranking of options using approximate and accurate methods, is implemented using a computer that ranks the options and identifies the most effective of them. The stage of data processing can be performed both on the server and on the user's computer itself.

After the data processing step is completed, the results obtained are provided to the end user in any format suitable for him. The results of the execution can be stored on the server, other media from which it is possible to read it further, or can be provided to the user's computer screen directly using a web browser or any other software tool that allows you to view information.

Examples of the implementation of the method.

The problem of finding relevant pages on the Internet with selection and ranking based on the principle of superposition

The task of searching for relevant pages on the Internet, ranking based on the idea of superposition can be implemented as follows. First, fast (approximate) methods exclude obviously irrelevant pages. These irrelevant pages can be, for example, those pages that do not belong to a given topic, contain spam, viruses, advertising, content that is undesirable for the user, phishing (Internet fraud) and more. Then, on the remaining much smaller set of pages, more subtle (accurate) ranking methods are applied, which, however, require large computational resources (slow). The irrelevant pages mentioned above can never be relevant to the user's query, which means that their use in more time-consuming methods is redundant and simply unnecessary. In this example, the superposition of some set of fast but approximate methods (used to cut off only the most irrelevant pages) and some set of exact methods (used for the final ranking of a small number of alternatives) gives a gain in the speed and accuracy (relevance) of the final ranking. In particular, for irrelevant pages, there is no need to conduct a detailed ranking, it is enough to assign them all the same rank (the last place in the ranking).

Table 1
Comparison of the exact selection procedure (Pareto Rule) and the four-step method based on the idea of superposition
№	Number of words from the query in the document title	The number of words from the query in the entire document	Boolean model (presence of all query words in the document)	Pareto Rule	superposition model
Stage 1. Suprathreshold heading selection	Stage 2. Above-threshold selection by document	Stage 3. Above-threshold choice according to the Boolean model	Stage 4. Pareto
1	1	6	1	0	1	1	1	0
2	2	10	1	1	1	1	1	1
3	4	7	0	0	1	1	0	0
4	0	3	1	0	0	0	0	0
5	3	9	1	1	1	1	1	1
6	4	8	1	1	1	1	1	1
7	1	1	0	0	1	1	0	0
8	0	0	0	0	0	0	0	0
9	1	0	0	0	1	0	0	0
10	0	0	0	0	0	0	0	0
11	0	0	0	0	0	0	0	0
12	0	0	0	0	0	0	0	0
13	0	0	0	0	0	0	0	0
14	0	0	0	0	0	0	0	0
15	0	2	0	0	1	0	0	0
16	0	0	0	0	0	0	0	0
17	0	1	0	0	0	0	0	0
18	0	0	0	0	0	0	0	0
19	0	0	0	0	0	0	0	0
20	0	0	0	0	0	0	0	0
21	0	0	0	0	0	0	0	0
22	0	0	0	0	0	0	0	0
23	0	1	0	0	0	0	0	0
24	0	0	0	0	0	0	0	0
25	0	0	0	0	0	0	0	0
26	0	0	0	0	0	0	0	0
27	0	0	0	0	0	0	0	0
28	0	0	0	0	0	0	0	0
29	0	1	0	0	0	0	0	0

Table 1 shows the simplest example of using two methods for choosing options - the Pareto rule and a four-step selection method based on the idea of superposition. In the task, it is necessary to determine which of the options are the most relevant (suitable) for the user's entered query. Each option is evaluated according to three criteria: the number of words from the query in the title of the document, the number of words from the query in the entire document, a boolean model (the presence of all query words in the document). In the example, the choice is made from 29 options.

If you use the usual Pareto rule, then the relevant documents will be documents No. 2, 5, 6. When using the Pareto rule, each option must be compared with all other options, i.e. each of the 29 options must be compared with each other. This means that the more options there are in the sample, the greater the computational complexity of this rule, which leads to the need to use simpler (approximate) selection rules.

However, the Pareto rule can be applied using a method of selecting and ranking effective options based on the idea of superposition. Table 1 shows a four-stage selection method that consists of successively applying three above-threshold rules, after which the Pareto rule is applied.

At the first stage, all options (documents) are excluded, in the title of which there is not a single word from the request. Thus, the number of options is reduced from 29 to 8.

At the second stage, those options are excluded for which no words from the query were found in the main part of the document. Then the number of options is reduced from 8 to 6. After that, only those documents are selected that contain all the words from the query. As a result, the number of options is reduced to 4. After that, the Pareto rule is applied for the remaining options, and the final choice includes only 3 options (documents) - No. 2, 5, 6.

In this example, the results of both methods are the same. However, the computational complexity of the Pareto rule is much higher. Therefore, if the number of options is small, the choice of the selection and ranking method is not important (does not matter). However, in conditions where the number of options reaches several million, it is necessary to use the second method, based on the idea of superposition, because it allows you to combine simple and complex selection rules, which reduces the computational complexity of the method.

In a number of models, in order to present the most interesting and sought-after offer to social network participants, it is necessary to segment user groups according to their common interests or according to the intensity of information exchange between them. In this case, for example, the threshold cut-off according to the rule "no more than one contact in the last year" (for a certain set of goods and services) allows you to immediately narrow the number of options within the group to a level acceptable for more complex algorithms. Of course, the presence of more than one contact per year does not imply a community of interests of users, i.e. deliberately inefficient options for grouping (segmentation) of social network participants according to their interests are cut off, with a simultaneous and sharp decrease in the size of the group.

Thus, the presented method allows the selection and ranking of options with high accuracy, especially in the presence of a large number of options characterized by a large set of indicators, since it allows a combination of approximate and exact procedures.

The claimed method can be used in the selection of effective options in search, recommender systems, decision support systems, Internet networks, systems for automatic classification of data packets and in other related areas.

In addition, the invention can be used in solving the problem of learning to rank, that is, the problem of choosing options with pre-known estimates of their usefulness according to criteria, for example, when evaluating the performance of enterprises, retail outlets and other objects in related areas.

Appendix 1. List of selection rules given in the work of F.T. Aleskerov, E. Kurbanov "On the degree of manipulation of the rules of collective choice", Automation and Telemechanics, 1998, No. 10, 134-146.

1. Plurality rule

The choice includes alternatives that are the best for the largest number of criteria, i.e.

those. means the number of criteria for which the alternative a ranks at least q-th place in their ordering. So if q=1 then a is the best alternative for criterion i; if q=2 then a- either the first or second best alternative, etc. The number q will be called the procedure level.

those. alternatives are selected that are among the q best for the maximum number of criteria.

This selection rule has linear computational complexity; for ranking, the computational complexity of the rule depends on the value of q. For q<

3. Threshold rule

Let ν 1 (x) be the number of criteria for which x is the worst alternative in their orderings, ν 2 (x) be the number of criteria for which x is the second worst alternative, and so on, ν m (x) be the number of criteria, for which alternative x is the best. The alternatives are then ordered lexicographically. It is said that alternative x V - dominates alternative y if ν 1 (x)< ν 1 (y) или, если существует k≤m такое, что ν i (x)= ν i (y), i=1, …, k-1, и ν k (x)< k (y). Другими словами, в первую очередь сравниваются количества последних мест в упорядочениях для каждой альтернативы, в случае, когда они равны, идет сравнение количества предпоследних мест, и так далее. Выбором являются альтернативы, недоминируемые по V.

This selection and ranking rule has linear computational complexity.

4. Borda rule

Each alternative x∈A is assigned a number r i (x , P →) equal to the cardinality of the set of alternatives worse than x in the criterion P i ∈ P → , i.e. r i (x , P →) = | L i (x) | = | ( b ∈ A: x P i b ) | . The sum of these values for i∈N is called the Borda rank of the alternative x,

The choice includes alternatives with the highest ranking

5. Black procedure

If there is a Condorcet winner, then it is declared by the collective choice, otherwise the Borda rule is used.

6. Coombs procedure.

The variant considered to be the worst by the maximum number of voters is excluded. Then the profile is narrowed down to a new set X and the procedure continues until only non-excluded options remain. Note here the difference between Coombs' rule and the vote transfer system. In the Coombs rule, the worst options are crossed out, while in the transfer system, the best options for the minimum number of voters are crossed out.

This selection and ranking rule has linear computational complexity.

7. Hara procedure

For each alternative, the number of first places in orderings by criteria is counted. Next, the alternatives with the least number of first places are eliminated from the voting. The procedure is repeated until the choice remains non-empty.

This selection and ranking rule has linear computational complexity.

8. Reverse Majority Rule

The choice includes alternatives that are the worst for the least number of criteria.

This selection and ranking rule has linear computational complexity.

9. Copland's first rule

For each alternative, two indicators are considered: the sum of the numbers of alternatives that are worse than the given one for each criterion, and the sum of the numbers of alternatives that are better than the given one for each criterion. The collective choice includes alternatives with the greatest difference between these two indicators.

A given selection rule has a linear computational complexity, for ranking, the computational complexity of the rule is highly dependent on the input data and is quadratic in the worst case.

10. Reverse Borda procedure (with transfer of votes)

For each alternative, the Board rank is calculated. Then the alternative with the lowest rank is eliminated. Board ranks are recalculated for multiple alternatives with no eliminated alternative. The procedure is repeated until the choice is non-empty.

For selection, the computational complexity of the rule is quadratic in the worst case. For ranking, the computational complexity of the rule is at least quadratic.

11. Nanson's rule

The Board rank for all variants is calculated. Then the average Borda score is calculated and only those x options for which the Borda score is below the average are excluded. Then the set X=A\(x) is constructed and the procedure is applied to the narrowed profile /X. The procedure continues until only non-excluded options remain. For selection, the computational complexity of the rule is quadratic in the worst case. For ranking, the computational complexity of the rule is at least quadratic.

12. Minimal Dominating Set

The set of alternatives Q is dominant if and only if any alternative in Q dominates any alternative outside of Q by the majority relation.

A dominant set is minimal if none of its own subsets is dominant. The collective choice is the minimum dominating set, if there is one, or their union, if there are several. This selection and ranking rule has a computational complexity of at least quadratic.

13. Minimal non-dominated set

The set of alternatives Q is non-dominated if and only if there is no alternative outside of Q that dominates any alternative from the set Q.

A non-dominated set is minimal if none of its own subsets is non-dominated. The collective choice is the minimal non-dominated set, if there is one, or their union, if there are several. This selection and ranking rule has a computational complexity of at least quadratic.

14. Minimal weakly stable set

The set of alternatives Q is weakly stable if and only if the existence of an alternative y outside Q that dominates an alternative x in Q implies the existence of an alternative z in Q such that z dominates Y.

A weakly stable set is minimal if none of its proper subsets is weakly stable. The collective choice is the minimal weakly stable set, if there is one, or their union, if there are several of them.

This selection and ranking rule has a computational complexity of at least quadratic.

75. Fishburne's rule

Let us construct a new binary relation y in which x dominates y if and only if the upper contour of the alternative x is a proper subset of the upper contour of the alternative y.

The collective choice will be the set of alternatives that are not dominated by y.

This selection and ranking rule has a computational complexity of at least quadratic.

16. Uncovered set I.

Let us construct a new binary relation 5 in which x dominates y if and only if the lower contour of the alternative y is a proper subset of the lower contour of the alternative x.

The collective choice will be the set of alternatives that are not dominated by 8.

This selection and ranking rule has a computational complexity of at least quadratic.

17. Uncovered set II

Alternative x B - dominates alternative y if x dominates y by a majority ratio and the upper contour of alternative x is a subset of the upper contour of alternative y. The collective choice includes alternatives that are not dominated with respect to B. This selection and ranking rule has a computational complexity of at least quadratic.

18. Richelson's Rule

A new binary relation σ is constructed in which x dominates y if and only if

The bottom contour y is a subset of the bottom contour x

The top contour x is a subset of the top contour y

In one of the two cases above, the occurrence occurs as a "own subset"

The collective choice includes non-dominated alternatives.

This selection and ranking rule has a computational complexity of at least quadratic.

19. Copland's first rule

The collective choice includes alternatives with the maximum power difference between the lower circuit and the upper circuit.

This selection and ranking rule has a computational complexity of at least quadratic.

20. Copland's second rule

The collective choice includes alternatives with the maximum capacity of the lower circuit.

This selection and ranking rule has a computational complexity of at least quadratic.

21. Copland's third rule

The collective choice includes alternatives with the minimum power of the upper circuit.

This selection and ranking rule has a computational complexity of at least quadratic.

22. Two-step majority rule

First, the simple majority rule is used (i.e., the option that receives more than 50% of the votes - first places - in the ordering of voters) is selected. If such a variant is found, then the procedure stops. If there is no such option, then two options are selected that received more votes than the other options (if there are more than two, then the two with the lowest numbers are taken). Then, assuming that the opinions of voters regarding these options (when deleting the rest) do not change, we again apply the rule of simple majority / votes - already on a two-element set.

Since individual opinions are presented as linear orders, there is always (for an odd number of voters) a single winning option.

This selection and ranking rule has linear computational complexity.

First, the simple majority rule is used (i.e., the option that receives more than 50% of the votes is selected). If such a variant is found, then the procedure stops. If there is no such variant, then variant x, which received the minimum number of votes, is deleted from the list.

The procedure is then applied again to the set X=A\(x and the /X profile. This selection and ranking rule has linear computational complexity.

24. Young procedure

If there is a Condorcet winner for the profile, then it is selected and the procedure stops there. If there is no such option, then all possible coalitions are considered, on which there are partial Condorcet winners. Next, the function u(x) is defined as the power of the maximal coalition in which x is the Condorcet winner.

Then the options with the maximum value of ux are selected:

This selection and ranking rule has a computational complexity of at least quadratic.

25. Simpson procedure (maximum procedure)

Let us construct a matrix S + such that ∀ a, b∈X, S + =(n(a,b)), where

n(a, b)=card(i∈N|aP i b), n(a,a)=+ ∞.

This selection and ranking rule has a computational complexity of at least quadratic.

26. Minimax procedure

Let us construct a matrix S such that ∀ a,b∈X, S + =(n(a,b)), n(a,a)=-∞.

Collective choice is defined as

This selection and ranking rule has a computational complexity of at least quadratic.

27. Strong q-Pareto simple majority rule

Let f(P → ;i;q)=(X∈A-||card(D ↓ i(x))≤q) determine q+1 options from maximum to below in linear order P i . Let ℑ=(I⊂N-||card(I)=) (Where the function [χ] means the minimum integer greater than or equal to x) be the family of simple majority coalitions. We introduce a function that selects an option that is among the top options for each voter in at least one simple majority coalition, and start with q=0. If there is no such option for q=0, then the choice by simple majority coalitions is reviewed again with q increased by one (i.e. weights q=1), etc., until the choice is empty. From this non-empty set, the option with the smallest number is selected, which is accepted as a collective choice.

This selection and ranking rule has exponential computational complexity.

28. Strong q-Pareto majority rule

This rule is similar to rule 26, with the addition that if several options are chosen, then for each of them the number of coalitions that have chosen it is counted. Then options with the maximum value of this indicator are selected.

The options with the maximum value of this indicator are selected. This selection and ranking rule has exponential computational complexity.

29. Strongest q-Pareto simple majority rule

We introduce the function

C (A) = ∩ I ∈ ℑ f (P → ; I ; q)

where f (P → ; I ; q) = ( χ ∈ A − | | c a r d (∩ ↓ i (x) ]) ≤ q ) , c a r d (I) = [ n / 2 ] optimal in each simple majority coalition, and start with q=0. If there are no such elements, then the case q=1, q=2, etc. is considered until the choice is not empty. From this non-empty set, the option with the smallest number is selected, which is taken as a collective choice. This selection and ranking rule has exponential computational complexity.

30. The rule of suprathreshold choice

Let the criterion φ(x), φ:A→R 1 be set on the set A, and the threshold function V: 2 A →R 1 be set on the set 2 A, which assigns the threshold level V(X) to each Xe2A set.

The suprathreshold selection rule is represented as the following expression:

n ¯s t: y ∈ C (X) ⇔ (y ∈ X & ϕ (y) ≥ V (X)) .

This selection rule has a linear computational complexity; for ranking, the computational complexity depends on the input data, in the worst case no higher than the quadratic one.

1. A method for selecting and ranking effective variants of search results, which consists in preliminarily forming criteria for assessing the relevance of a search result variant to a search query and specifying a finite number of search result variants or a set of procedures for selecting and ranking search results variants and the sequence of their execution for selecting results variants search results evaluated as the most effective, evaluate each of the search results options according to the relevance to the search query criteria, on the basis of which the search result options are ranked by assigning a rank to each of them from the condition of matching the largest number of criteria in descending order; sequentially selecting and ranking variants of search results using the superposition method in at least two stages, if the number of variants of search results in the remaining group of variants of search results corresponds to a predetermined finite number of variants of search results for selection or all specified selection procedures are used, selection of variants of search results and their ranking is stopped and the search result options from the selected group are evaluated as the most effective, if the number of search result options in the remaining group of search result options does not match the predetermined final number of search result options for selection, the selection of search result options and their ranking continue, while selection of search result options, their ranking and exclusion is carried out until the specified number of search result options is reached or until all the specified selection procedures are used and the selected group of options is evaluated as the most effective.

2. The method according to claim 1, characterized in that at the first stage, search results options are selected if there are a large number of them by the superposition method using selection and ranking methods characterized by linear computational complexity O(n), and the group of search results options is excluded , which have the lowest rank.

3. The method according to claim 1, characterized in that at the second and subsequent stages, criteria for evaluating the search query are formed, on the basis of which the variants of the search results are ranked and the variants of the search results are selected from the remaining array processed at the previous stage by the superposition method using methods, whose computational complexity is not lower than quadratic O(n 2) and exclude the next group of search results with a lower rank.

4. A method for selecting and ranking effective variants of search results, which consists in preliminarily forming criteria for assessing the relevance of a search result variant to a search query and specifying a finite number of search result variants for selection, evaluated as the most effective, evaluating each of the variants of search results by relevance search query criteria, on the basis of which the variants of search results are ranked by assigning a rank to each of them from the condition of matching the largest number of criteria in descending order; the selection and ranking of search result variants are sequentially selected and ranked by the superposition method in at least two stages, if the number of search result variants in the remaining group of search result variants corresponds to a predetermined finite number of search result variants for selection, the selection of search result variants and their ranking are stopped and the variants search results from the selected group are evaluated as the most effective, if the number of search result options in the remaining group of search result options does not match the predetermined final number of search result options for selection, the selection of search result options and their ranking continue, while the selection of search result options, their ranking and exclusion are carried out until the specified number of search results options is reached, the selected group of search results options is evaluated as the most effective.

5. The method according to claim 4, characterized in that at the first stage, search results options are selected if there are a large number of them by the superposition method using selection and ranking methods characterized by linear computational complexity O(n), and the group of search results options is excluded , which have the lowest rank.

6. The method according to claim 4, characterized in that, at the second and subsequent stages, search query evaluation criteria are formed, on the basis of which search result options are ranked and search result options are selected from the remaining array processed at the previous stage by the superposition method using methods, whose computational complexity is not lower than quadratic O(n 2) and exclude the next group of search results with a lower rank.

7. The method according to claim 4, characterized in that a set of procedures for selecting and ranking variants of search results and the sequence of their execution are additionally specified.

8. A method for selecting and ranking effective variants of search results, which consists in preliminarily forming criteria for assessing the relevance of a search result variant to a search query and specifying a set of procedures for selecting and ranking variants of search results and the sequence of their execution to select search results variants evaluated as the most effective evaluating each of the variants of the search results according to the relevance to the search query criteria, on the basis of which the variants of the search results are ranked by assigning a rank to each of them from the condition of matching the largest number of criteria in descending order; the search results variants are sequentially selected and ranked by the superposition method in at least two stages, the search results variants are selected, their ranking and exclusion are carried out until all the specified selection procedures are used and the selected group of search results variants is evaluated as the most effective.

9. The method according to claim 8, characterized in that at the first stage, search results options are selected if there are a large number of them by the superposition method using selection and ranking methods characterized by linear computational complexity O(n), and the group of search results options is excluded , which have the lowest rank.

10. The method according to claim 8, characterized in that, at the second and subsequent stages, search query evaluation criteria are formed, on the basis of which search result options are ranked and search result options are selected from the remaining array processed at the previous stage by the superposition method using methods, whose computational complexity is not lower than quadratic O(n 2) and exclude the next group of search results with a lower rank.

11. The method according to claim 8, characterized in that it additionally sets a finite number of search results options for selection, evaluated as the most effective.

12. The method according to claim 8, characterized in that, in order to select the most effective group of options for search results, additional selection and ranking methods and the sequence of their execution are specified, and the selection and ranking are repeated.

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The invention relates to computer technology. EFFECT: high speed of selection and accuracy of search results. A method for selecting and ranking effective variants of search results, which consists in preliminarily forming criteria for assessing the relevance of a search result variant to a search query and specifying a finite number of search result variants or a set of procedures for selecting and ranking search results variants and the sequence of their execution for selecting search results variants, evaluated as the most effective, evaluate each of the variants of the search results according to the relevance to the search query criteria, on the basis of which the variants of the search results are ranked by assigning a rank to each of them from the condition of matching the largest number of criteria in descending order; sequentially select and rank search result options by the superposition method, at least in two stages, if the number of search result options in the remaining group of search result options corresponds to a predetermined finite number of search result options for selection or all specified selection procedures are used, selection of options search results and their ranking are stopped and the search result options from the selected group are evaluated as the most effective, if the number of search result options in the remaining group of search result options does not match the predetermined final number of search result options for selection, the selection of search result options and their ranking continue. 3 n. and 9 z.p. f-ly, 1 ill.

Analysis of the best and most efficient use of the object of assessment. Choosing the most efficient way to use the property Choosing the most efficient possible

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1.1 Descriptionlandsite

The description of the land plot is presented in the table below.

Table 1.1 - Description of the land plot

Functional zoning of the site in accordance with the General Plan

1.2 Description of improvements

The description of the improvements is presented in the table below.

Table 1.2 - Description of land improvements

1.3 History of the object

Rice.

For many laureates, the victory at the Sviridov competition was a good start in their professional development.

2 .Analysisenvironmentalenvironments

2.1 Analysislocationsobject

Rice.

Territory development

The territory of the quarter in which the object under study is located is limited to:

- Yesenin Street;

- Prospect of Enlightenment;

-Ivan-Fomin street;

- Lilac boulevards.

The study area is distinguished by an abundance of parks.

The largest of them are Sosnovka Park, with a well-groomed forest, walking paths, playgrounds and volleyball courts, the Forest Engineering Academy Park, located near Muzhestva Square.

Figure 2.1 - Local location of the object

Residential development

general information

In the early years of the city's existence, the Vyborg side was considered a frontier. At the forefront of the city, this territory was part of the St. Petersburg part, then became an independent Finnish, then Vyborg side.

Various industrial enterprises appear on the outskirts - sugar, tanneries, breweries; shipyard, barracks, prisons. Right there on the embankments of the Neva, tsarist dignitaries - G. Teplov, A. Bezborodko, Admiral A. Sinyavin and others are building summer cottages.

Transport accessibility of the Vyborgsky district can be generally described as satisfactory.

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