Genetic algorithm for chance constrained reliability stochastic optimisation problems

Vincent Charles and A. Udhayakumar

International Journal of Operational Research, 2012, vol. 14, issue 4, 417-432

Abstract: 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.

Keywords: redundancy optimisation; system reliability; stochastic simulation; GAs; genetic algorithms; Monte Carlo simulation; redundancy allocation; reliability optimisation; chance constraints. (search for similar items in EconPapers)
Date: 2012
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