Abstract

Using equilibrium chance measures, this paper presents a new version of fuzzy random dependent-chance programming models. Also, a fuzzy random simulation approach is designed for computing equilibrium chance of a fuzzy random event. At the end of this paper, we suggest a hybrid intelligent algorithm, which integrates fuzzy random simulation, neural network and genetic algorithm for solving fuzzy random dependent-chance programming models.

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