A Genetic Algorithm Approach for Reliability of Bridge Network in Fuzzy System

Abstract

This paper presents a Genetic Algorithm (GA) approach for solving constrained reliability optimization problem of the five unit bridge network. Considering uncertainty for cost, the reliability optimization problem has been solved by GA technique to maximize system reliability. GA is an efficient method for solving this type of optimization problems. This paper successfully applies the GA technique to obtain the optimal solution of the complex system reliability model under cost constraint in fuzzy environment in which the system cost and component costs might be imprecise. Triangular fuzzy number is used to represent the fuzzy cost coefficients. Static penalty method has been used to handle the cost constraint of the problem. To solve the reliability optimization model, we have developed the GA using MATLAB with tournament selection process, elitism mechanism, arithmetic crossover and uniform mutation operations. Finally, computational results are presented for the reliability of bridge network in crisp and fuzzy environment.