Methodology for searching multi-criteria solutions based on digital twins
https://doi.org/10.35854/1998-1627-2023-7-851-858
Abstract
Aim. To justify and propose a methodology for searching multi-criteria Pareto-optimal solutions based on the use of socio-economic models or digital twins of complex dynamical systems.
Tasks. To substantiate the relevance of using predictive methods for making managerial decisions in conditions of rapid changes and the need to use for these purposes recommendation systems using socio-economic models or digital twins. To propose a methodology for searching multi-criteria Pareto-optimal solutions and to evaluate its accuracy on mathematical and socioeconomic models. To formulate recommendations and limitations on the use of this methodology.
Methods. General scientific methods (analysis, synthesis, grouping), mathematical methods of searching for Pareto-optimal solutions and generation of LP -sequences, results of mathematical modelling and numerical experiments were used in the research.
Results. The methodology of searching for multicriteria Pareto-optimal managerial decisions is proposed, proposals and limitations on its application are formulated.
Conclusions. In conditions of rapid changes it is important to be able to make managerial decisions that take into account the influence of many factors and, accordingly, many criteria characterising the socio-economic system, and at the same time it is necessary to make these managerial decisions in accordance with the logic “from the future”. The method of searching for multi-criteria Pareto-optimal solutions based on the use of socio-economic models or digital twins is proposed. The accuracy of this method is investigated on mathematical models of different degrees of nonlinearity with different number of parameters when solving production multi-parametric problems.
About the Authors
A. D. StolyarovRussian Federation
Alexander D. Stolyarov - postgraduate student
31 Kashirskoe highway, Moscow 115409
V. V. Gordeev
Russian Federation
Vladimir V. Gordeev - CEO
3 Kotlyakovskaya st., bldg. 13, Moscow 115201
V. I. Abramov
Russian Federation
Victor I. Abramov - D.Sc. in Economics, PhD in Physical and Mathematical Sciences, Associate Professor, Professor at the Department of Business Project Management
31 Kashirskoe highway, Moscow 115409
References
1. Abramov V.I., Andreev V.D. Analysis of strategies for digital transformation of Russian regions in the context of achieving national goals. Voprosy gosudarstvennogo i munitsipal’nogo upravleniya = Public Administration Issues. 2023;(1):89-119. (In Russ.). DOI: 10.17323/1999-5431-2023-0-1-89-119
2. Covin J.G., Selvin D.P. Strategic management of small firms in hostile and benign environments. Strategic Management Journal. 1989;10(1):75-87. DOI: 10.1002/smj.4250100107
3. Abramov V.I. Methodology for assessing innovative potential. Doct. econ. sci. diss. St. Petersburg: St. Petersburg State University of Economics and Finance; 2012. 302 p. (In Russ.).
4. Abramov V.I. Genesis of innovative potential. Teoriya i praktika obshchestvennogo razvitiya = Theory and Practice of Social Development. 2012;(10):231-234. (In Russ.).
5. Abramov V.I., Lavrentiev I.A., Grempel V.O. The role of innovations and startups in the development of ecosystems. Ekonomicheskie nauki = Economic Sciences. 2022;(210):97-100. (In Russ.). DOI: 10.14451/1.210.97
6. Stolyarov A.D., Gordeev V.V., Abramov V.I. Model of a module for dynamic generation of personalized offers of additional services for airline passengers. Ekonomika i upravlenie = Economics and Management. 2023;29(3):335-344. (In Russ.). DOI: 10.35854/1998-1627-2023-3-335-344
7. Abramov V.I., Gromyko A.A. Digital twin of a smart city as a modern trend of the digital economy. In: State and society of Russia in the context of modern geopolitical challenges: Innovations, economics, prospects. Proc. 12th All-Russ. sci.-pract. conf. Cheboksary: Novoe vremya; 2021:215-220. (In Russ.).
8. Yarotskaya E.V. Economic-mathematical methods and modeling. Saratov: IPR Media; 2018. 227 p. (In Russ.).
9. Ershov E.K. et al. Optimization methods. St. Petersburg: St. Petersburg State University of Architecture and Civil Engineering; 2016. 89 p. (In Russ.).
10. Zuikova A. What are digital twins and how they are used. RBC Trends. URL: https://trends.rbc.ru/trends/industry/6107e5339a79478125166eeb (accessed on 23.06.2023). (In Russ.).
11. Abramov V.I., Golovin O.L., Stolyarov A.D. Methodology of searching Pareto-optimal solutions for the development of smart cities on the basis of their digital twins. Sovremennaya ekonomika: problemy i resheniya = Modern Economics: Problems and Solutions. 2021;(9):8- 15. (In Russ.). DOI: 10.17308/meps.2021.9/2666
12. Kovaleva K.A., Kumratova A.M., Velikanova O.L., Klintsevich R.I. On the properties of nonlinearity of dynamic socio-economic systems and processes. Sovremennaya ekonomika: problemy i resheniya = Modern Economics: Problems and Solutions. 2020;(12):27-34. (In Russ.). DOI: 10.17308/meps.2020.12/2487
Review
For citations:
Stolyarov A.D., Gordeev V.V., Abramov V.I. Methodology for searching multi-criteria solutions based on digital twins. Economics and Management. 2023;29(7):851-858. (In Russ.) https://doi.org/10.35854/1998-1627-2023-7-851-858