Display options
Cite
Govindan K, Jafarian A, Azbari ME, et al. Optimal Bi-Objective Redundancy Allocation for Systems Reliability and Risk Management. IEEE Trans Cybern. 2015;46(8):1735-48doi: 10.1109/TCYB.2014.2382666.
Govindan, K., Jafarian, A., Azbari, M. E., & Choi, T. M. (2016). Optimal Bi-Objective Redundancy Allocation for Systems Reliability and Risk Management. IEEE transactions on cybernetics, 46(8), 1735-48. https://doi.org/10.1109/TCYB.2014.2382666
Govindan, Kannan, et al. "Optimal Bi-Objective Redundancy Allocation for Systems Reliability and Risk Management." IEEE transactions on cybernetics vol. 46,8 (2016): 1735-48. doi: https://doi.org/10.1109/TCYB.2014.2382666
Govindan K, Jafarian A, Azbari ME, Choi TM. Optimal Bi-Objective Redundancy Allocation for Systems Reliability and Risk Management. IEEE Trans Cybern. 2016 Aug;46(8):1735-48. doi: 10.1109/TCYB.2014.2382666. Epub 2015 Jan 23. PMID: 25622333.
Copy Download .nbib Format: NLM
Share it on

IEEE Trans Cybern. 2016 Aug;46(8):1735-48. doi: 10.1109/TCYB.2014.2382666. Epub 2015 Jan 23.

Optimal Bi-Objective Redundancy Allocation for Systems Reliability and Risk Management.

IEEE transactions on cybernetics

Kannan Govindan, Ahmad Jafarian, Mostafa E Azbari, Tsan-Ming Choi

PMID: 25622333 DOI: 10.1109/TCYB.2014.2382666

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.

Publication Types