A knowledge-based archive multi-objective simulated annealing algorithm to optimize series–parallel system with choice of redundancy strategies. (February 2015)

• Record Type: Journal Article
• Authors: Zaretalab, Arash; Hajipour, Vahid; Sharifi, Mani; Shahriari, Mohammad Reza
• Is Part Of: Computers & industrial engineering. Volume 80(2015)
• Page Start: 33
• Page End: 44
• Publication Date: 2015-02
• Subjects: Reliability -- Redundancy allocation problem -- Knowledge-based archive multi-objective simulated annealing algorithm; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2014.11.008
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: 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. Abstract: 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.