An Algorithm for Fuzzy Random Chance-Constrained Programming

H. Wang, R. Zhao, and Y. Ning (PRC)


Simultaneous perturbation stochastic approximation (SPSA); fuzzy random variables; fuzzy random simula tion; chance-constrained programming


In fuzzy random environments, the basic idea for mod elling chance-constrained programming is to maximize the optimistic value to the return with fuzzy random variables subject to some chance constraints. In solving these mod els, in general, it is impossible to compute the optimistic value and chances of fuzzy random variables due to the complexity of fuzzy random variables. In such cases, it is very necessary to use fuzzy random simulation to estimate these values. To solve fuzzy random chance-constrained programming, this paper proposes an algorithm by embed ding fuzzy random simulation in simultaneous perturbation stochastic approximation (SPSA) algorithm. At the end of this paper, an numerical example illustrates the effective ness of the presented algorithm.

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