Availability allocation and multi-objective optimization for parallel-series systems

Cheng Hsiung Chiang, Liang-Hsuan Chen

Research output: Contribution to journalArticle

28 Citations (Scopus)

Abstract

Availability allocation is required when the manufacturer is obliged to allocate proper availability to various components in order to design an end product to meet specified requirements. This paper proposes a new multi-objective genetic algorithm, namely simulated annealing based multi-objective genetic algorithm (saMOGA), to resolve the availability allocation and optimization problems of a repairable system, specifically a parallel-series system. Compared with a general multi-objective genetic algorithm, the major feature of the saMOGA is that it can accept a poor solution with a small probability in order to enlarge the searching space and avoid the local optimum. The saMOGA aims to determine the optimal decision variables, i.e. failure rates, repair rates, and the number of components in each subsystem, according to multiple objectives, such as system availability, system cost and system net profit. The proposed saMOGA is compared with three other multi-objective genetic algorithms. Computational results showed that the proposed approach could provide higher solution quality and greater computing efficiency.

Original languageEnglish
Pages (from-to)1231-1244
Number of pages14
JournalEuropean Journal of Operational Research
Volume180
Issue number3
DOIs
Publication statusPublished - 2007 Aug 1

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All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Modelling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

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