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Soft Computing

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20.02.2019 | Methodologies and Application

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

verfasst von: Ryoji Tanabe, Hisao Ishibuchi

Erschienen in: Soft Computing | Ausgabe 23/2019

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Abstract

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.

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Strictly speaking, the differences between MOEA/D-DE (Li and Zhang 2009) and the original MOEA/D (Zhang and Li 2007) are as follows: (i) the parent individuals are selected from the whole population with some probability, (ii) the number of individuals replaced by a child is restricted, and (iii) the DE variation operator is used in Li and Zhang (2009).

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Titel: Review and analysis of three components of the differential evolution mutation operator in MOEA/D-DE
verfasst von: Ryoji Tanabe
Hisao Ishibuchi
Publikationsdatum: 20.02.2019
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 23/2019
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-019-03842-6

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