Multi-objective gravitational search algorithm based on decomposition

被引：0
|
作者：
Bi, Xiaojun [1 ]
Diao, Pengfei [1 ]
Wang, Yanjiao [2 ]
Xiao, Jing [3 ]
机构：
[1] College of Information and Communication Engineering, Harbin Engineering University, Harbin
[2] College of Information Engineering, Northeast Dianli University, Jilin, 132001, Jilin
[3] Dept. of Information Engineering, Liaoning Provincial College of Communications, Shenyang
来源：
Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology | 2015年 / 47卷 / 11期
关键词：
Decomposition; Gravitational search algorithm (GSA); Multi-objective optimization; Multi-population strategy;
D O I：
10.11918/j.issn.0367-6234.2015.11.012
中图分类号：
学科分类号：
摘要：
When the ideal frontier is discontinuous or inhomogeneous, the multi-objective evolutionary algorithm can't solve multi-objective problems effectively by decomposition. In order to improve this situation, a novel multi-objective gravitational search algorithm based on decomposition (MOGSA/D) is proposed. In MOGSA/D, the multi-population serial strategy is good for the population study evolutionary information. According to shape prediction of ideal frontier, a suitable generation method of weight coefficient is selected. A pruning strategy is adopted to prune the solution set. Experimental results show that MOGSA has a good performance to solve multi-objective problems in comparison with other multi-objective optimization algorithms. © 2015, Harbin Institute of Technology. All right reserved.
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页码：69 / 75
页数：6
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