INFORMATION MODELING OF DEVELOPMENT PROCESSES BASED ON THE SYSTEM ANALYSIS OF "BOTTLENECKS"

Purpose: the purpose of the presented research is to expand the possibilities of using information-logical models for the analysis of forecasting "bottlenecks" and quantitative assessment of ways to eliminate them in the development of socio-economic systems.

Methods: the implementation of this research is based on the use of basic principles, properties and rules of construction of phased informationlogical models for solving complex problems. Their development involves the introduction of quantitative assessments of ways to reduce the negative potential of "bottlenecks" and comparing the expected results of their elimination with the initial state.

Results: the authors presented a method of analytical directed search and elimination of "bottlenecks" in the development of complex systems. This method is based on the use of rules for building information-logical models. A quantitative analysis of the potential for reducing the potential of identified "bottlenecks" assumes the construction of a linear graph based on the information-logical model, as well as the calculation of integral estimates of the expected compensation of the initial potential of "bottlenecks".

conclusions and Relevance: the developed method of analytical representation of the possibilities of eliminating "bottlenecks" in the development of socio-economic systems is applicable for the analysis of the prospects of eliminating "bottlenecks" on the basis of building a scheme of a full cycle of decision-making. Testing of the presented approach on the example of analysis of known problem situations showed that the proposed tools allow a priori to evaluate the effectiveness of the proposed mechanisms, simulate their expansion and effectiveness in terms of impact on the final result. This increases the possibilities for finding effective solutions to complex scientific, technological and socioeconomic problems. In addition, it will be very useful in the examination of various projects and programs.

1. Ackoff R.L., Emery F.E. On purposeful systems: An interdisciplinary analysis of individual and social behavior as a system of purposeful events. Piscataway: Aldine Transaction Publ., 2005. 303 p. (Russ. ed.: Ackoff R.L., Emery F.E. O tseleustremlennykh sistemakh. Moscow: LKI Publ., 2008. 269 p.) (in Eng.)

2. Optner S.L. System Analysis for Business and Industrial Problem Solving. Prentice-Hall, Inc., Englewood Cliffs, New Jersey, 1965. 116 р. (in Russ.)

3. Balaian G.G., ZHarikova G.G., Komkov N.I. Informacionno-logicheskie modeli nauchnyh issledovanij [Information-logical models of scientific research]. М.: Nauka, 1978 (in Russ.)

4. Komkov N.I. Matematicheskie modeli nauchnyh issledovanij i razrabotok [Mathematical models of research and development]. М.: Nauka, 1978 (in Russ.)

5. Berge Claude. Theorie des graphes etses Applications. Collection universitaire de Mathematiques, n° 2. Paris, Dunod, 1958, VIII p. 277 p. (in Eng.)

6. Yanch E. Prognozirovanie nauchno-tekhnicheskogo progressa [Forecasting scientific and technological progress]. M.: Progress, 1970. 569 р. (in Russ.)

7. Ivanter V.V., Komkov N.I. The forecast scientific and technological development: state, problems and prospects. Innovations. 2006; (10):42—52 (in Russ.)

8. Forrester J.W. World dynamics. N.Y.: Productivity Press Publ., 1979. 242 p. (Russ. ed.: Forrester, J. Mirovaya dinamika. Moscow: AST Publ.; St. Petersburg: Terra Fantastica Publ., 2003. 379 p.)

9. Nagin Daniel. Group-Based Modeling of Development. Harvard University Press, 2005. DOI: https://doi.org/10.4159/9780674041318 (in Eng.)

10. Li Q., Chen YL. System Development and Integration Methodology. In: Modeling and Analysis of Enterprise and Information Systems. Springer, Berlin, Heidelberg. 2009. DOI: https://doi.org/10.1007/978-3-540-89556-5_3 (in Eng.)

11. Clements M.P. and Hendry D.F. Forecasting Economic Time Series. Cambridge University Press, 1998. DOI: https://doi.org/10.1017/CBO9780511599286 (in Eng.)

12. Reynolds, Martin and Holwell, Sue. Introducing systems approaches. In: Reynolds, Martin and Holwell, Sue eds. Systems Approaches to Managing Change: A Practical Guide. London: Springer, 2010, p. 1-23. DOI: https://doi.org/10.1007/978-184882-809-4_1 (in Eng.)

13. Cartwright Nancy. Scientific models versus social reality. Building Research & Information. 2015; 44(3):334-337. DOI: https://doi.org/10.1080/09613218.2015.1083811 (in Eng.)

14. The logical foundations of scientific theories: languages, structures, and models / by Daecio Krause and Jonas R.B. Arenhart. Description: New York: Routledge, 2017. 162 p. DOI: https://doi.org/10.4324/9781315535210 (in Eng.)