A many-objective evolutionary algorithm with reference point-based and vector angle-based selection

Chen Yu Lee, Jia Fong Yeh, Tsung Che Chiang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper we proposed a many-objective evolutionary algorithm by combining the reference point-based selection in NSGA-III and the vector angle-based selection in VaEA. Performance of the proposed algorithm is verified by testing on the negative version of four DTLZ functions. The proposed algorithm is better than NSGA-III and is comparable to VaEA in terms of IGD. Besides, the proposed algorithm is more robust and can expand the front better.

Original languageEnglish
Title of host publicationGenetic and Evolutionary Computing - Proceedings of the 11th International Conference on Genetic and Evolutionary Computing
EditorsShu-Chuan Chu, Jerry Chun-Wei Lin, Chien-Ming Chen, Jeng-Shyang Pan
PublisherSpringer Verlag
Pages3-11
Number of pages9
ISBN (Print)9789811064869
DOIs
Publication statusPublished - 2018 Jan 1
Event11th International Conference on Genetic and Evolutionary Computing, 2017 - Kaohsiung, Taiwan
Duration: 2017 Nov 62017 Nov 8

Publication series

NameAdvances in Intelligent Systems and Computing
Volume579
ISSN (Print)2194-5357

Other

Other11th International Conference on Genetic and Evolutionary Computing, 2017
CountryTaiwan
CityKaohsiung
Period17/11/617/11/8

Keywords

  • EMO
  • Evolutionary algorithm
  • Many-objective
  • Multiobjective
  • NSGA-III

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

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  • Cite this

    Lee, C. Y., Yeh, J. F., & Chiang, T. C. (2018). A many-objective evolutionary algorithm with reference point-based and vector angle-based selection. In S-C. Chu, J. C-W. Lin, C-M. Chen, & J-S. Pan (Eds.), Genetic and Evolutionary Computing - Proceedings of the 11th International Conference on Genetic and Evolutionary Computing (pp. 3-11). (Advances in Intelligent Systems and Computing; Vol. 579). Springer Verlag. https://doi.org/10.1007/978-981-10-6487-6_1