Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/55938
Title: Optimal bi-objective redundancy allocation for systems reliability and risk management
Authors: Govindan, K
Jafarian, A
Azbari, ME
Choi, TM 
Keywords: Meta-heuristic algorithms
Multiobjective optimization
Reliability optimization
Systems risk management
Issue Date: 2014
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on cybernetics, 2014, v. 46, no. 8, p. 1735-1748 How to cite?
Journal: IEEE transactions on cybernetics 
Abstract: In the big data era, systems reliability is critical to effective systems risk management. In this paper, a novel multiobjective approach, with hybridization of a known algorithm called NSGA-II and an adaptive population-based simulated annealing (APBSA) method is developed to solve the systems reliability optimization problems. In the first step, to create a good algorithm, we use a coevolutionary strategy. Since the proposed algorithm is very sensitive to parameter values, the response surface method is employed to estimate the appropriate parameters of the algorithm. Moreover, to examine the performance of our proposed approach, several test problems are generated, and the proposed hybrid algorithm and other commonly known approaches (i.e., MOGA, NRGA, and NSGA-II) are compared with respect to four performance measures: 1) mean ideal distance; 2) diversification metric; 3) percentage of domination; and 4) data envelopment analysis. The computational studies have shown that the proposed algorithm is an effective approach for systems reliability and risk management.
URI: http://hdl.handle.net/10397/55938
ISSN: 2168-2267
EISSN: 2168-2275
DOI: 10.1109/TCYB.2014.2382666
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