Genetic algorithm for chance constrained reliability stochastic optimisation problems

Vincent Charles, A. Udhayakumar

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

8 Citas (Scopus)


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 simulationbased 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. Copyright © 2012 Inderscience Enterprises Ltd.
Idioma originalEspañol
Páginas (desde-hasta)417-432
Número de páginas16
PublicaciónInternational Journal of Operational Research
EstadoPublicada - 1 ene. 2012

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