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Optimization of constrained multiple-objective reliability problems using evolutionary algorithms

Author

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  • Salazar, Daniel
  • Rocco, Claudio M.
  • Galván, Blas J.

Abstract

This paper illustrates the use of multi-objective optimization to solve three types of reliability optimization problems: to find the optimal number of redundant components, find the reliability of components, and determine both their redundancy and reliability. In general, these problems have been formulated as single objective mixed-integer non-linear programming problems with one or several constraints and solved by using mathematical programming techniques or special heuristics. In this work, these problems are reformulated as multiple-objective problems (MOP) and then solved by using a second-generation Multiple-Objective Evolutionary Algorithm (MOEA) that allows handling constraints. The MOEA used in this paper (NSGA-II) demonstrates the ability to identify a set of optimal solutions (Pareto front), which provides the Decision Maker with a complete picture of the optimal solution space. Finally, the advantages of both MOP and MOEA approaches are illustrated by solving four redundancy problems taken from the literature.

Suggested Citation

  • Salazar, Daniel & Rocco, Claudio M. & Galván, Blas J., 2006. "Optimization of constrained multiple-objective reliability problems using evolutionary algorithms," Reliability Engineering and System Safety, Elsevier, vol. 91(9), pages 1057-1070.
    • Handle: RePEc:eee:reensy:v:91:y:2006:i:9:p:1057-1070
    DOI: 10.1016/j.ress.2005.11.040
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