On a method of solving of possibilistic-probabilistic programming problems

Yu. E. Egorova

Tver State University, Tver

Abstract: The paper studies possibilistic-probabilistic optimization problems, based on the principle of expected possibility, and a method for solving its stochastic analogue in the case of the weakest t-norm describing the interaction of fuzzy parameters. The conditions that are easier to verify and ensure the convergence of the method of stochastic quasigradients of the solution of an equivalent stochastic analog are obtained.

Keywords: possitbilistic-probabilistic optimization, stochastic quasi-gradient method, fuzzy random variable, the weakest t-norm.

UDC: 510.676, 519.7

Received: 25.12.2020
Revised: 06.05.2021

DOI: 10.26456/fssc77

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