Multi-objective redundancy allocation optimization using a variable neighborhood search algorithm |
| |
Authors: | Yun-Chia Liang Min-Hua Lo |
| |
Institution: | 1.Department of Industrial Engineering and Management,Yuan Ze University,Taoyuan County,Taiwan, ROC |
| |
Abstract: | A variable neighborhood search (VNS) algorithm has been developed to solve the multiple objective redundancy allocation problems
(MORAP). The single objective RAP is to select the proper combination and redundancy levels of components to meet system level
constraints, and to optimize the specified objective function. In practice, the need to consider two or more conflicting objectives
simultaneously increases nowadays in order to assure managers or designers’ demand. Amongst all system level objectives, maximizing
system reliability is the most studied and important one, while system weight or system cost minimization are two other popular
objectives to consider. According to the authors’ experience, VNS has successfully solved the single objective RAP (Liang
and Chen, Reliab. Eng. Syst. Saf. 92:323–331, 2007; Liang et al., IMA J. Manag. Math. 18:135–155, 2007). Therefore, this study aims at extending the single objective VNS algorithm to a multiple objective version for solving
multiple objective redundancy allocation problems. A new selection strategy of base solutions that balances the intensity
and diversity of the approximated Pareto front is introduced. The performance of the proposed multi-objective VNS algorithm
(MOVNS) is verified by testing on three sets of complex instances with 5, 14 and 14 subsystems respectively. While comparing
to the leading heuristics in the literature, the results show that MOVNS is able to generate more non-dominated solutions
in a very efficient manner, and performs competitively in all performance measure categories. In other words, computational
results reveal the advantages and benefits of VNS on solving multi-objective RAP. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|