A knowledge-based archive multi-objective simulated annealing algorithm to optimize series–parallel system with choice of redundancy strategies

•An efficient multi-objective algorithm based on SA is presented to solve MORAP.•The algorithm called knowledge-based archive MOSA (KBAMOSA) algorithm.•KBAMOSA used a memory matrix to reinforce the neighborhood structure.•KBAMOSA algorithm dominated the solutions obtained by NSGA-II.•KBAMOSA is supe...

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Bibliographic Details
Published in:Computers & industrial engineering Vol. 80; pp. 33 - 44
Main Authors: Zaretalab, Arash, Hajipour, Vahid, Sharifi, Mani, Shahriari, Mohammad Reza
Format: Journal Article
Language:English
Published: New York Elsevier Ltd 01.02.2015
Pergamon Press Inc
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ISSN:0360-8352, 1879-0550
Online Access:Get full text
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Summary:•An efficient multi-objective algorithm based on SA is presented to solve MORAP.•The algorithm called knowledge-based archive MOSA (KBAMOSA) algorithm.•KBAMOSA used a memory matrix to reinforce the neighborhood structure.•KBAMOSA algorithm dominated the solutions obtained by NSGA-II.•KBAMOSA is superior to AMOSA algorithm based on standard metrics. Redundancy allocation problem (RAP) is one of the best-developed problems in reliability engineering studies. This problem follows to optimize the reliability of a system containing s sub-systems under different constraints, including cost, weight, and volume restrictions using redundant components for each sub-system. Various solving methodologies have been used to optimize this problem, including exact, heuristic, and meta-heuristic algorithms. In this paper, an efficient multi-objective meta-heuristic algorithm based on simulated annealing (SA) is developed to solve multi-objective RAP (MORAP). This algorithm is knowledge-based archive multi-objective simulated annealing (KBAMOSA). KBAMOSA applies a memory matrix to reinforce the neighborhood structure to achieve better quality solutions. The results analysis and comparisons demonstrate the performance of the proposed algorithm for solving MORAP.
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ISSN:0360-8352
1879-0550
DOI:10.1016/j.cie.2014.11.008