Genetic algorithm for chance constrained reliability stochastic optimisation problems Online publication date: Sun, 11-Jan-2015
by Vincent Charles; A. Udhayakumar
International Journal of Operational Research (IJOR), Vol. 14, No. 4, 2012
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.
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