Evolutionary many-objective optimization by MO-NSGA-II with enhanced mating selection

Shao Wen Chen, Tsung-Che Chiang

研究成果: 書貢獻/報告類型會議貢獻

3 引文 斯高帕斯(Scopus)

摘要

Many-objective optimization deals with problems with more than three objectives. The rapid growth of non-dominated solutions with the increase of the number of objectives weakens the search ability of Pareto-dominance-based multiobjective evolutionary algorithms. MO-NSGA-II strengthens its dominance-based predecessor, NSGA-II, by guiding the search process with reference points. In this paper, we further improve MO-NSGA-II by enhancing its mating selection mechanism with a hierarchical selection and a neighborhood concept based on the reference points. Experimental results confirm that the proposed ideas lead to better solution quality.

原文英語
主出版物標題Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014
發行者Institute of Electrical and Electronics Engineers Inc.
頁面1397-1404
頁數8
ISBN(電子)9781479914883
DOIs
出版狀態已發佈 - 2014 九月 16
事件2014 IEEE Congress on Evolutionary Computation, CEC 2014 - Beijing, 中国
持續時間: 2014 七月 62014 七月 11

出版系列

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

其他

其他2014 IEEE Congress on Evolutionary Computation, CEC 2014
國家中国
城市Beijing
期間14/7/614/7/11

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Theoretical Computer Science

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  • 引用此

    Chen, S. W., & Chiang, T-C. (2014). Evolutionary many-objective optimization by MO-NSGA-II with enhanced mating selection. 於 Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014 (頁 1397-1404). [6900400] (Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CEC.2014.6900400