Fuzzy Random Age-Dependent Replacement Policy

A fuzzy random variable is a function from a probability space to the set of fuzzy variables. In this paper, an age-dependent replacement policy is studied in which the lifetimes of components are treated as fuzzy random variables. The fuzzy random age-dependent replacement policy was discussed and a fuzzy random simulation technique to estimate the long run expected cost per unit time is developed. In order to find the best T-age replacement policy to minimize the long run expected cost per unit time, a fuzzy random expected value model is presented. Furthermore, the simultaneous perturbation stochastic approximation (SPSA) algorithm based on fuzzy random simulation is designed to get the optimal solution of the proposed models. At the end of this paper, a numerical example is enumerated.