A two-stage approach for multi-objective decision making with applications to system reliability optimization

Zhaojun Li, Haitao Liao, David W. Coit

Research output: Contribution to journalArticle

70 Scopus citations

Abstract

This paper proposes a two-stage approach for solving multi-objective system reliability optimization problems. In this approach, a Pareto optimal solution set is initially identified at the first stage by applying a multiple objective evolutionary algorithm (MOEA). Quite often there are a large number of Pareto optimal solutions, and it is difficult, if not impossible, to effectively choose the representative solutions for the overall problem. To overcome this challenge, an integrated multiple objective selection optimization (MOSO) method is utilized at the second stage. Specifically, a self-organizing map (SOM), with the capability of preserving the topology of the data, is applied first to classify those Pareto optimal solutions into several clusters with similar properties. Then, within each cluster, the data envelopment analysis (DEA) is performed, by comparing the relative efficiency of those solutions, to determine the final representative solutions for the overall problem. Through this sequential solution identification and pruning process, the final recommended solutions to the multi-objective system reliability optimization problem can be easily determined in a more systematic and meaningful way.

Original languageEnglish (US)
Pages (from-to)1585-1592
Number of pages8
JournalReliability Engineering and System Safety
Volume94
Issue number10
DOIs
StatePublished - Oct 1 2009

Keywords

  • Data envelopment analysis
  • Multi-objective optimization
  • Self-organizing map
  • System reliability

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Industrial and Manufacturing Engineering

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