Genetic algorithm for chance constrained reliability stochastic optimisation problems (Q2627308)

Summary: This paper addresses the chance constrained reliability stochastic optimisation problem, in which the objective is to maximise system reliability for the given chance constraints. A problem specific stochastic simulation-based genetic algorithm (GA) is developed for finding optimal redundancy to an \(n\)-stage series system with \(m\)-chance constraints of the redundancy allocation problem. As GA is a proven robust evolutionary optimisation search technique for solving various reliability optimisation problems and the Monte Carlo (MC) simulation, which is a flexible tool for checking feasibility of chance constraints, we have effectively combined GA and MC simulation in the proposed algorithm. The effectiveness of the proposed algorithm is illustrated for a four-stage series system with two chance constraints.