Cooperative Co-Evolution With Formula Based Grouping and CMA for Large Scale Optimization

被引：5
|
作者：
Liu, Haiyan [1 ]
Guan, Shiwei [1 ]
Liu, Fangjie [1 ]
Wang, Yuping [1 ]
机构：
[1] Xidian Univ, Sch Comp Sci & Technol, Xian 710071, Shanxi, Peoples R China
来源：
2015 11TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY (CIS) | 2015年
关键词：
large scale optimization; cooperative co-evolution; decomposition; white-box grouping; covariance matrix adaptation; EVOLUTION STRATEGY; ADAPTATION;
D O I：
10.1109/CIS.2015.76
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Cooperative co-evolution framework is widely used in large scale optimization problems. Usually, the large scale problem is divided into smaller sub groups using black-box decomposition methods based on variable interactions. However these black-box decomposition methods have limitations in finding correct variable interactions. In this paper, a white-box decomposition method named formula based grouping(FBG) is adopted and further improved. Also, we extend the covariance matrix adaptation to work with FBG under the cooperative co-evolution framework. Based on it, a new evolutionary algorithm is proposed for handling large scale optimization problems. The numerical experiments on CEC' 2013 benchmark suit shows the efficiency of the proposed algorithm.
引用
收藏
页码：282 / 285
页数：4
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