Review and analysis of three components of the differential evolution mutation operator in MOEA/D-DE

Tanabe, Ryoji; Ishibuchi, Hisao

2019-12

10.1007/s00500-019-03842-6

SOFT COMPUTING   影响因子和分区

1432-7643

1433-7479

A decomposition-based multi-objective evolutionary algorithm with a differential evolution variation operator (MOEA/D-DE) shows high performance on challenging multi-objective problems (MOPs). The DE mutation consists of three key components: a mutation strategy, an index selection method for parent individuals, and a bound-handling method. However, the configuration of the DE mutation operator that should be used for MOEA/D-DE has not been thoroughly investigated in the literature. This configuration choice confuses researchers and users of MOEA/D-DE. To address this issue, we present a review of the existing configurations of the DE mutation operator in MOEA/D-DE and systematically examine the influence of each component on the performance of MOEA/D-DE. Our review reveals that the configuration of the DE mutation operator differs depending on the source code of MOEA/D-DE. In our analysis, a total of 30 configurations (three index selection methods, two mutation strategies, and five bound-handling methods) are investigated on 16 MOPs with up to five objectives. Results show that each component significantly affects the performance of MOEA/D-DE. We also present the most suitable configuration of the DE mutation operator, which maximizes the effectiveness of MOEA/D-DE.

Multi-objective optimization Decomposition-based evolutionary algorithms Differential evolution operators Implementation of algorithms

SCI ; EI

英语

第一 ; 通讯

Program for University Key Laboratory of Guangdong Province[2017KSYS008]

Computer Science

Computer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications

WOS:000495070400045

SPRINGER

20190906543903

Multiobjective optimization

Optimization Techniques:921.5

COMPUTER SCIENCE

Web of Science

Southern Univ Sci & Technol, Shenzhen Key Lab Computat Intelligence, Univ Key Lab Evolving Intelligent Syst Guangdong, Dept Comp Sci & Engn, Shenzhen 518055, Peoples R China

Tanabe, Ryoji,Ishibuchi, Hisao. Review and analysis of three components of the differential evolution mutation operator in MOEA/D-DE[J]. SOFT COMPUTING,2019,23(23):12843-12857.

Tanabe, Ryoji,&Ishibuchi, Hisao.(2019).Review and analysis of three components of the differential evolution mutation operator in MOEA/D-DE.SOFT COMPUTING,23(23),12843-12857.

Tanabe, Ryoji,et al."Review and analysis of three components of the differential evolution mutation operator in MOEA/D-DE".SOFT COMPUTING 23.23(2019):12843-12857.