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Dynamic model of the software development market based on the assignment problem on pain points
 
PIIS042473880017518-8-1
DOI10.31857/S042473880017518-8
Publication type Article
Status Published
Authors
Ilya Lesik 
Occupation: Senior Engineer
Affiliation: Joint-Stock Company «Scientific and Production Association Russian basic information technology
Address: Moscow, Russian Federation
Aleksandr Perevozchikov
Occupation: Senior Research Scholar
Affiliation: Joint-Stock Company «Scientific and Production Association Russian basic information technology
Address: Russian Federation
Journal nameEkonomika i matematicheskie metody
EditionVolume 57 Issue 4
Pages108-116
Abstract

The authors propose the formulation of a discrete dynamic model of the software developmentmarket (SM) based on the assignment problem (AP) on pain points (PP), which can also be obtained according to the scheme used in (Vasin, Grigorieva, Lesik, 2018), if we abandon the integer number of elements of the assignment matrix. However, there are also features: equilibrium prices can be calculated directly, and therefore a variational formulation of the internal problem of determining equilibrium prices based on Debreu's theorem (Debreu, 1954) is not required. The functions of changing the phase coordinates can be taken convex, for example, the norm of the difference in the square, and do not take into account the constant costs for each control switching. Such a statement is also given in this paper. If we have a dynamic expansion of the AP on PP, it is possible to determine the additional profit of the transport system through the use of futures. Formulas for the components of the gradient of the indicator are obtained. This allows us to organize a gradient method for solving a dynamic AP on PP. The authors also demonstrate an approximate algorithm and a model example of its use for solving the dynamic expansion of the AP on PP, based on solving the current static problem with an increment of those elements of the efficiency matrix that coincide with the corresponding elements of the optimal assignment matrix, if we abandon the integer nature of the assignment matrix. This is equivalent to randomization of the assignment problem, when the corresponding assignments are implemented with certain probabilities, which are used to determine the error of the approximate algorithm by comparing it with the exact solution obtained with the gradient method for sufficiently large values of penalty constants.

Keywordsdynamic problem of assignment on pain points, phase constraints , method of penalty functions, Hamilton-Pontryagin’s function, conjugate system, components of the gradient, gradient method of the exact solution, approximate algorithm for solving the dynamic problem
Received17.11.2021
Publication date13.12.2021
Number of characters18511
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1. Ashmanov S.A. (1981). Linear programming. Moscow: Nauka (in Russian).
2. Debreu G. (1954). Valuation equilibrium and Pareto optimum. Proceedings of the National Acad-emy of Sciences of the USA, 40, 588–592.
3. Ding X., Wang K., Gibbons P.B., Zhang X. (2012). BWS: Balanced work stealing for time-sharing multicores. Proceedings of the 7th ACM European Conferees on Computer Systems. New York: EuroSys, 12, 365–378.
4. Fedorov V.V. (1979). Numerical methods of maximin. Moscow: Nauka (in Russian).
5. Ford L., Falkerson D. (1966). Streams in networks. Moscow: Mir (in Russian).
6. Korbut A.A., Finkil'shtein Yu.Yu. (1969). Discrete programming. D.B. Yudin (ed.). Moscow: Nauka (in Russian).
7. Lesik I.A., Perevozchikov A.G. (2016). Determination of the optimal production volumes and sales prices in the linear model of multiproduct monopoly. Economics and Mathematical Methods, 52, 1,140–148 (in Russian).
8. Lesik I.A., Perevozchikov A.G. (2020). Dynamic model of investments in research of oligopolia. Economics and Mathematical Methods, 56, 2, 102–114 (in Russian).
9. Makarov V.L., Rubinov F.M. (1973). Mathematical theory of economic dynamics and equili-brium. Moscow: Nauka (in Russian).
10. Mesoeconomics of development (2011). G.B. Kleiner (ed.). Moscow: Nauka (in Russian).
11. Perevozchikov A.G., Lesik I.A. (2014). Non-stationary model of investment in fixed assets of the enterprise. Applied Mathematics and Informatics. Scientific Works of Computational Mathe-matics and Cybernetics Department, MSU. Moscow: MAKS Press, 46, 76–88 (in Russian).
12. Poljak B.T. (1983). Introduction to Optimization. Moscow: Nauka (in Russian).
13. Sergienko A.M., Simonenko V.P., Simonenko A.V. (2016). Improved assignment algorithm for task schedulers in heterogeneous distributed computing systems. System Research and infor-mation technologies, 2, 20–35 (in Russian).
14. Ustyuzhanina E.V., Dementiev V.E., Evsukov S.G. (2021). Digital transaction platforms: Ensur-ing their efficiency. Economics and Mathematical Methods, 57, 1, 5–18 (in Russian).
15. Vasil'ev F.P. (1981). Methods for solving extremal problems. Moscow: Nauka (in Russian).
16. Vasin A.A., Grigor'eva O.M., Lesik I.A. (2017). Applied Mathematics and Informatics. Scientific Works of Computational Mathematics and Cybernetics Department, MSU, 55, 74–90 (in Russian).
17. Vasin A.A., Grigor'eva O.M., Lesik I.A. (2018). The task of optimizing the transport system of the energy market. In: The collection of the IX Moscow International Conference on Opera-tions Research (ORM2018). Proceedings. Responsible editors: A.A. Vasin, A.F. Izmailov, 247–251 (in Russian).
18. Vasin A.A., Grigor'eva O.M., Tsyganov N.I. (2017). Optimization of the transport system of the energy market. Reports of the Academy of Sciences, 475, 4, 377–381 (in Russian).
19. Vasin A.A., Morozov V.V. (2005). Game theory and models of mathematical economics. Moscow: MAKS Press (in Russian).

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