AN ALGORITHM FOR FUZZY RANDOM CHANCE-CONSTRAINED PROGRAMMING

摘要

In fuzzy random environments, the basic idea for modelling chance-constrained programming is to maximize the optimistic value to the return with fuzzy random variables subject to some chance constraints. In solving these models, 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 embedding fuzzy random simulation in simultaneous perturbation stochastic approximation (SPSA) algorithm. At the end of this paper, an numerical example illustrates the effectiveness of the presented algorithm.