A SPSA Algorithm for Solving Fuzzy Random Expected Value Models

In this paper, fuzzy random expected value models are considered. In order to solve the models, a simultaneous perturbation stochastic approximation (SPSA) algorithm based on fuzzy random simulation is proposed, in which fuzzy random simulation technique is designed to estimate the expected values of functions with fuzzy random variables, and SPSA is used to search for the optimal solution. At the end of this paper, an example illustrates the feasibility and effectiveness of the provided algorithm

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