The use of fuzzy cognitive maps in the development of an experimental model of automation of production accounting of material flows

Automation of enterprise management on the basis of economic and mathematical models, information technology is one of the main stages of development for all enterprises. The use of cognitive modeling allows making management decisions under uncertainty. The article considers the construction of an experimental model of automation of production accounting of material flows based on the use of fuzzy cognitive maps. The algorithm of cognitive modeling is presented. The main advantages of cognitive tools are noted: 1) the ability to study the fine structure of management decisions (the necessary sequence of management actions, the necessary degree of activity of these actions, the study of the dynamic stability of strategies, etc.); 2) the opportunity to explore the dynamics of management decisions at a qualitative level, without attracting for this purpose hard-to-access and not always reliable quantitative information, which is extremely important in a rapidly changing business environment and the growing pace of technological innovation.

It is emphasized that none of the known management support tools has the above capabilities. Cognitive dynamic analysis significantly expands the tool base of management, based today mainly on the means of static situational analysis and prescription schemes of decision-making.

In the construction of the experimental model, the target factors of the cognitive map are determined, the connectivity analysis is carried out and the process of propagation of disturbances on the graph is studied.

The analysis showed that the proposed model is quite efficient and can be used to predict economic activity and determine the expected values of a number of parameters that need to be monitored to diagnose trends in the development of an industrial enterprise. The results of the work should be considered as a solution to a number of management tasks.

1. Anisimov Y.P., Zhuravlev Yu.V., Kuskov I.V., Chuklinov V.A. Usloviya razvitiya innovatsionnogo potentsiala [Conditions of development of innovative potential]. Voronezh: UGUET, 2011. 450 p. (In Russ.)

2. Barmashov K.S., Barmashovo L.V., Viktorova T.S. Formirovanie ekonomicheskogo mehanizma innovatsionnoinvestitsionnogo protsessa v usloviah ustoichivogo razvitiya predpriyatiya [The formation of the economic mechanism of innovative-investment process in terms of sustainable development of the enterprise]. Vyazma: filial FGBOU VPO «MGIU», 2013. 120 p. (In Russ.)

3. Tukkel I.L. Upravlenie innovatsionnimy proektami [Management of innovative projects]. St. Petersburg: BHV-Petersburg, 2011. 416 p. (In Russ.)

4. Sipowicz L.Yu. Innovations as the tool of overcoming of crisis and the basis of economic development. Vestnik Chelyabinskogo gosudarstvennogo universiteta = Bulletin of Chelyabinsk State University. 2011. No. 32. Pp. 15–21. (In Russ.)

5. Alpeyeva E.A., Ryabtseva I.F. Progress and innovation: an analysis of system condition. Economicheski analis: theoriya i practika = Economic analysis: theory and practice. 2012. № 18(273). Pp. 37–41. (In Russ.)

6. Artemov R.V., Kolmykova T.S., Shirokova L.V., Kharchenko E.V. Upravlenie razvitiem malogo i srednego biznesa v regione v usloviyah sectoral`noi divergentsii [Management of development of small and mediumsized businesses in the region in terms of sectoral divergence]. Kursk: Yugo-Zapadnyi gosudarstvennyi universitet, 2015. 151 p. (In Russ.)

7. Automation of management processes: we increase the efficiency of the company. Available at: https://www.gd.ru/articles/9757-avtomatizatsiyaprotsessov-upravleniya (accessed: 22.12.2018). (In Russ.).

8. Dilman A. Myths and reality of implementation of MES-systems. Direktor informatsionnoy slujbi = Director of Information Services. 2012. No. 1. (In Russ.)

9. Zagidullin R.R. Upravlenie mashinostroitel`nim proizvodstvom s pomosh`u system MES, APS, ERP [Management of machine-building production with the help of MES, APS, ERP systems]. Stary Oskol: TNT, 2011. 372 p. (In Russ.)

10. Marenko V.A., Maltseva M.I. Cognitive modeling application for analyzing small businesses problems. Izvestiya Irkutskoi gosudarstvnnoi academii = News of the Irkutsk State Economic Academy. 2015. Vol. 25. No. 6. Pp. 1014–1024. (In Russ.)

11. Karayev R.A., Mihailova R.N., Safarly I.I., Sadikhova N.Y., Imamverdiyeva X.F. Cognitive tools for dynamic analysis of enterprise business strategies. Business-Informatika = Bisiness Informatics. 2018. No. 1(43). Pp. 7–16. (In Russ.). DOI: 10.17323/19980663.2018.1.7.16

12. Savchuk O.V., Ladanyuk A.P., Gerasimenko T.M. Fuzzy cognitive modeling in the control system of technological complexes dairy industry. Novyi Universitet. Seriya: tekhnicheskie nauki = New University. Technical sciences. 2015. № 1-2(35-36). Pp. 13–19. (In Russ.). DOI: 10.15350/2221-9552.2015.1-2

13. Kulinich A.A. System of cognitive modeling Kanva. Available at: http://www.raai.org/about/persons/kulinich/pages/kanva2003.html (accessed: 21.01.2019). (In Russ.)

14. Maksimov V.I., Karnaushenko E.K., Kachaev S.V. Cognitive technologies for support of managerial decision-making. Available at: http://www.iis.ru/ events/19981130/maximov.ru. (accessed: 05.01.2019). (In Russ.)

15. Silov V.B. Prinyatie strategicheskih resheni v nechetkoi obstanovke [The strategic decision-making in a fuzzy environment]. Moscow: INPRO – RES, 1995. 228 p. (In Russ.)

16. Shirokova L.V., Alpeyeva E.A. Improvement of tools and mechanisms of innovative development of corporate forms of business in the region. Social`noeconomicheskie yavleniya i protsessi = Social and Economic Phenomena and Processes. 2014. Vol. 9. No. 11. Pp. 185– 193. (In Russ.).

17. Makarenko D.I. Models and methods of strategic management of the military-industrial complex. Summary of Cand. Diss. (Econ.). Moscow, 2006. 24 p. (In Russ.)

18. Vasilenko T.G. O. Henry and cognitive maps. Education portal, LLC «Organization of Time». Available at: http://www.improvement.ru/zametki/cognitive (accessed: 22.12.2018). (In Russ.).

19. Strokova L.A. Use of fuzzy cognitive maps when developing base rated models. Izvestiya tomskogo polytechnicheskogo universiteta = Bulletin of the Tomsk Polytechnic University. 2009. Vol. 314. No. 5. Pp. 95–100. (In Russ.)

20. Marenko V.A., Maltseva M.I Cognitive modeling application for analyzing small businesses problems. Izvestiya Baikal’skogo Gosudarstvennogo Universiteta = Bulletin of Baikal State University. 2015. Vol. 25. No. 6. Pp. 1014–1024. (In Russ.). DOI: 10.17150/19933541.2015.25(6).1014-1024

21. GOST R 51705.1-2001 «Quality Systems. Food quality management based on HACCP principles. General requirements». Moscow: STANDARTINFORM, 2013. (In Russ.)

22. GOST R ISO 22000-2007 «Food safety management Systems. Requirements for organizations involved in the food chain». Moscow: STANDARTINFORM, 2013. (In Russ.)