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

Chen Yu Lee; Jia Fong Yeh; Tsung Che Chiang

doi:10.1007/978-981-10-6487-6_1

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

Chen Yu Lee, Jia Fong Yeh, Tsung Che Chiang^*

^*Corresponding author for this work

Department of Computer Science and Information Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	Genetic and Evolutionary Computing - Proceedings of the 11th International Conference on Genetic and Evolutionary Computing
Editors	Shu-Chuan Chu, Jerry Chun-Wei Lin, Chien-Ming Chen, Jeng-Shyang Pan
Publisher	Springer Verlag
Pages	3-11
Number of pages	9
ISBN (Print)	9789811064869
DOIs	https://doi.org/10.1007/978-981-10-6487-6_1
Publication status	Published - 2018
Event	11th International Conference on Genetic and Evolutionary Computing, 2017 - Kaohsiung, Taiwan Duration: 2017 Nov 6 → 2017 Nov 8

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	579
ISSN (Print)	2194-5357

Other

Other	11th International Conference on Genetic and Evolutionary Computing, 2017
Country/Territory	Taiwan
City	Kaohsiung
Period	2017/11/06 → 2017/11/08

Keywords

EMO
Evolutionary algorithm
Many-objective
Multiobjective
NSGA-III

ASJC Scopus subject areas

Control and Systems Engineering
General Computer Science

Access to Document

10.1007/978-981-10-6487-6_1

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

A many-objective evolutionary algorithm with reference point-based and vector angle-based selection. / Lee, Chen Yu; Yeh, Jia Fong; Chiang, Tsung Che.
Genetic and Evolutionary Computing - Proceedings of the 11th International Conference on Genetic and Evolutionary Computing. ed. / Shu-Chuan Chu; Jerry Chun-Wei Lin; Chien-Ming Chen; Jeng-Shyang Pan. Springer Verlag, 2018. p. 3-11 (Advances in Intelligent Systems and Computing; Vol. 579).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Lee, CY, Yeh, JF & Chiang, TC 2018, A many-objective evolutionary algorithm with reference point-based and vector angle-based selection. in S-C Chu, JC-W Lin, C-M Chen & J-S Pan (eds), Genetic and Evolutionary Computing - Proceedings of the 11th International Conference on Genetic and Evolutionary Computing. Advances in Intelligent Systems and Computing, vol. 579, Springer Verlag, pp. 3-11, 11th International Conference on Genetic and Evolutionary Computing, 2017, Kaohsiung, Taiwan, 2017/11/06. https://doi.org/10.1007/978-981-10-6487-6_1

Lee CY, Yeh JF, Chiang TC. A many-objective evolutionary algorithm with reference point-based and vector angle-based selection. In Chu SC, Lin JCW, Chen CM, Pan JS, editors, Genetic and Evolutionary Computing - Proceedings of the 11th International Conference on Genetic and Evolutionary Computing. Springer Verlag. 2018. p. 3-11. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-981-10-6487-6_1

Lee, Chen Yu ; Yeh, Jia Fong ; Chiang, Tsung Che. / A many-objective evolutionary algorithm with reference point-based and vector angle-based selection. Genetic and Evolutionary Computing - Proceedings of the 11th International Conference on Genetic and Evolutionary Computing. editor / Shu-Chuan Chu ; Jerry Chun-Wei Lin ; Chien-Ming Chen ; Jeng-Shyang Pan. Springer Verlag, 2018. pp. 3-11 (Advances in Intelligent Systems and Computing).

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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.",

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N2 - 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.

AB - 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.

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

Abstract

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Keywords

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