Improving CIMDE with An Mixed Selection Method

被引：0

作者：

Chen Dan ^{[1
]}

Xia Dahai ^{[1
]}

Xiong Caiquan ^{[1
]}

Gu Wei ^{[1
]}

机构：

[1] Hubei Univ Technol, Comp Sch, Wuhan, Peoples R China

来源：

PROCEEDINGS OF 2020 IEEE 10TH INTERNATIONAL CONFERENCE ON ELECTRONICS INFORMATION AND EMERGENCY COMMUNICATION (ICEIEC 2020) | 2020年

关键词：

differential evolution; mutation operator; stagnation; selection; DIFFERENTIAL EVOLUTION;

D O I：

10.1109/iceiec49280.2020.9152316

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Differential evolution(DE) is a popular evolution algorithm. How to select individuals for mutation operators is a very critical problem. Many researchers proposed improved mutation operators by selecting more outstanding individuals to produce mutated vectors. Collective information-powered mutation operator based differential evolution(CIMDE) proposed an improved collective information-powered mutation operator that uses multiple outstanding individuals as the heuristic information to release the selection pressure. But we observed that the mutation operator will be easily trapped into stagnation. So an improved mixed mutation operator named "current or rand-to-ci_ m best/1" is proposed to help individuals to departure from stagnation. Experiments show that this operator can improve the performance of the algorithm on CEC2013 bentmark functions.

引用

页码：94 / 97

页数：4

共 6 条

[1]

[Anonymous], 2016, IEEE T CYBERNETICS

[2] Improving Differential Evolution With a Successful-Parent-Selecting Framework [J].