This paper presents the use of genetic algorithm to solve reliability redundancy allocation problem of complicated system in fuzzy environment. Generally, this problem has been formulated as single objective integer non-linear programming problem with several resource constraints. In this paper, the reliability of each component as well as other parameters related to the problem is considered to be fuzzy valued. In this work, the corresponding constrained optimization problem has been transformed to crisp constrained optimization problem using defuzzification of fuzzy number. Here, widely known Yager ranking Index has been used for defuzzification of fuzzy number. The Big-M penalty function technique has been used to transform the constrained optimization problem into an unconstrained optimization problem. The converted problem has been solved with the help of real coded genetic algorithm. To illustrate the proposed methodology, a numerical example has been considered and solved. To study the performance of the proposed genetic algorithm, sensitivity analyses have been done graphically.
Genetic Algorithm Based Approach for Reliability Redundancy Allocation Problems in Fuzzy Environment