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A replacement strategy for balancing convergence and diversity in MOEA/D

  • Zhenkun Wang*
  • , Qingfu Zhang
  • , Maoguo Gong
  • , Aimin Zhou
  • *此作品的通讯作者
  • Xidian University
  • City University of Hong Kong
  • University of Essex

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

This paper studies the replacement schemes in MOEA/D and proposes a new replacement named global replacement. It can improve the performance of MOEA/D. Moreover, trade-offs between convergence and diversity can be easily controlled in this replacement strategy. It also shows that different problems need different trade-offs between convergence and diversity. We test the MOEA/D with this global replacement on three sets of benchmark problems to demonstrate its effectiveness.

源语言英语
主期刊名Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014
出版商Institute of Electrical and Electronics Engineers Inc.
2132-2139
页数8
ISBN(电子版)9781479914883
DOI
出版状态已出版 - 16 9月 2014
活动2014 IEEE Congress on Evolutionary Computation, CEC 2014 - Beijing, 中国
期限: 6 7月 201411 7月 2014

出版系列

姓名Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014

会议

会议2014 IEEE Congress on Evolutionary Computation, CEC 2014
国家/地区中国
Beijing
时期6/07/1411/07/14

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