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Adjustment of weight vectors of penalty-based boundary intersection method in MOEA/D

  • City University of Hong Kong
  • Xi'an Jiaotong University

科研成果: 书/报告/会议事项章节会议稿件同行评审

10 引用 (Scopus)

摘要

Multi-objective Evolutionary Algorithm Based on Decomposition (MOEA/D) is one of the dominant algorithmic frameworks for multi-objective optimization in the area of evolutionary computation. The performance of multi-objective algorithms based on MOEA/D framework highly depends on how a diverse set of single objective subproblems are generated. Among all decomposition methods, the Penalty-based Boundary Intersection (PBI) method has received particular research interest in MOEA/D due to its ability for controlling the diversity of population for many-objective optimization. However, optimizing multiple PBI subproblems defined via a set of uniformly-distributed weight vectors may not be able to produce a good approximation of Pareto-optimal front when objectives have different scales. To overcome this weakness, we suggest a new strategy for adjusting weight vectors of PBI-based subproblems in this paper. Our experimental results have shown that the performance of MOEA/D-PBI with adjusted weight vectors is competitive to NSGA-III in diversity when dealing with the scaled version of some benchmark multi-objective test problems.

源语言英语
主期刊名Evolutionary Multi-Criterion Optimization - 10th International Conference, EMO 2019, Proceedings
编辑Sanaz Mostaghim, Kathrin Klamroth, Kalyanmoy Deb, Erik Goodman, Carlos A. Coello Coello, Kaisa Miettinen, Patrick Reed
出版商Springer Verlag
91-100
页数10
ISBN(印刷版)9783030125974
DOI
出版状态已出版 - 2019
活动10th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2019 - East Lansing, 美国
期限: 10 3月 201913 3月 2019

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
11411 LNCS
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议10th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2019
国家/地区美国
East Lansing
时期10/03/1913/03/19

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