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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| Veröffentlicht in: | Computers & industrial engineering Jg. 80; S. 33 - 44 |
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| Hauptverfasser: | , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
New York
Elsevier Ltd
01.02.2015
Pergamon Press Inc |
| Schlagworte: | |
| ISSN: | 0360-8352, 1879-0550 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | •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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| Bibliographie: | SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 0360-8352 1879-0550 |
| DOI: | 10.1016/j.cie.2014.11.008 |