An Improved Multi-objective Differential Evolution Algorithm

被引：0

作者：

Niu, Dapeng ^{[1
,2
]}

Wang, Fuli ^{[1
,2
]}

Chang, Yuqing ^{[1
]}

He, Dakuo ^{[1
]}

Gu, Dehao ^{[3
]}

机构：

[1] Northeastern Univ, Sch Informat Sci & Engn, Shenyang, Liaoning Provin, Peoples R China

[2] Northeastern Univ, State Key Lab Synthet Automat Process Ind, Shenyang, Liaoning Provin, Peoples R China

[3] Northeastern Univ, State Key Lab Rolling & Automat, Shenyang, Liaoning Provin, Peoples R China

来源：

PROCEEDINGS OF THE 2012 24TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC) | 2012年

基金：

中国国家自然科学基金;

关键词：

Multi-objective; differential evolution algorithm; chaotic initialization; adaptive mutation; approximation and uniformity; OPTIMIZATION;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Based on multi-objective differential evolution algorithm, adaptive chaotic multi-objective differential evolution algorithm(AC-DEMO) is proposed, combining with adaptive and chaotic principles. In AC-DEMO, chaotic initialization and adaptive mutation operator are introduced to improve the efficiency of the algorithm. Numerical experiment results of commonly used test functions show that the algorithm has a good approximation and uniformity index and is suitable to solve complex multi-objective optimization problems.

引用

页码：879 / 882

页数：4

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