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

页码：282 / 285

页数：4

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