OPTIMAL ALTERNATIVE SELECTION MODELS IN A MULTI-STAGE DECISION-MAKING PROCESS

Oksana Mulesa, Vitaliy Snytyuk, Ivan Myronyuk

Abstract


Management decision-making tasks are usually characterized by a high level of uncertainty. When solving this class of problems, it is necessary to take into account the environmental conditions for the implementation of the decisions made and the consequences that may arise in this case. The decision-making task in the face of uncertainty can be represented in the form of a “game with nature”, in which the optimal player strategy is sought.

A two-stage decision-making process is considered, in which at each stage the decision-making problem is solved in conditions of risk. The case is supposed in which, after making a decision at the first stage, choosing an effective alternative and the onset of a certain state of nature, it is necessary to solve the decision-making problem of the second stage.

Decision-making models based on well-known decision models of the “game with nature” are proposed. The developed models allow in the process of choosing an effective alternative to the first stage to assess the possible consequences of such a choice, taking into account the expectations of the decision maker.

In the course of experimental verification, it is shown that the developed decision-making models can be used to solve such multi-stage problems, the phased solution of which is incorrect. This may occur due to the fact that some of their stages are associated with certain losses, and others – with profit. In such situations, it is advisable to consider the problem as a whole and at each stage, take into account all available information as much as possible.


Keywords


hierarchical decision-making process; “game with nature”; decision-making models

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References


Murphy, A., Katz, R. W. (2019). Probability, statistics, and decision making in the atmospheric sciences. CRC Press, 547.

Hnatienko, H. M., Snytiuk, V. Ye. (2008). Ekspertni tekhnolohiyi pryiniattia rishen. Kyiv: TOV «Maklaut», 444.

Voloshyn, O. F., Mashchenko, S. O. (2010). Modeli ta metody pryiniattia rishen. Kyiv: Vydavnycho-polihrafichnyi tsentr «Kyivskyi universytet», 336.

Emets, O. A., Ust'yan, N. Yu. (2008). Igry s kombinatornymi ogranicheniyami. Kibernetika i sistemniy analiz, 4, 134–141.

Colman, A. M. (2016). Game theory and experimental games: The study of strategic interaction. Elsevier, 314.

Nowik, I., Nowik, T. (2017). Games with Costly Winnings. International Game Theory Review, 19 (04), 1750016. doi: https://doi.org/10.1142/s0219198917500165

Busemeyer, J. R., Wang, Z., Shiffrin, R. M. (2015). Bayesian model comparison favors quantum over standard decision theory account of dynamic inconsistency. Decision, 2 (1), 1–12. doi: https://doi.org/10.1037/dec0000017

Meier, K. J., Favero, N., Zhu, L. (2015). Performance Gaps and Managerial Decisions: A Bayesian Decision Theory of Managerial Action. Journal of Public Administration Research and Theory, 25 (4), 1221–1246. doi: https://doi.org/10.1093/jopart/muu054

Mulesa, O., Geche, F., Batyuk, A., Buchok, V. (2018). Development of Combined Information Technology for Time Series Prediction. Advances in Intelligent Systems and Computing, 361–373. doi: https://doi.org/10.1007/978-3-319-70581-1_26

Jing, L., Li, Z., Peng, X., Li, J., Jiang, S. (2019). A Relative Equilibrium Decision Approach for Concept Design Through Fuzzy Cooperative Game Theory. Journal of Computing and Information Science in Engineering, 19 (4). doi: https://doi.org/10.1115/1.4042837

Sitorus, F., Cilliers, J. J., Brito-Parada, P. R. (2019). An integrated constrained fuzzy stochastic analytic hierarchy process method with application to the choice problem. Expert Systems with Applications, 138, 112822. doi: https://doi.org/10.1016/j.eswa.2019.112822




DOI: http://dx.doi.org/10.21303/2461-4262.2019.001005

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ISSN 2461-4262 (Online), ISSN 2461-4254 (Print)