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Genetic algorithm for chance constrained reliability stochastic optimisation problems

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  • Vincent Charles
  • A. Udhayakumar

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.

Suggested Citation

  • Vincent Charles & A. Udhayakumar, 2012. "Genetic algorithm for chance constrained reliability stochastic optimisation problems," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 14(4), pages 417-432.
    • Handle: RePEc:ids:ijores:v:14:y:2012:i:4:p:417-432
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