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A Many-Objective Evolutionary Strategy Based on Angle Dominance

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DOI: 10.23977/acss.2023.070101 | Downloads: 16 | Views: 487

Author(s)

Yuhang Bi 1, Qinghua Zhao 2

Affiliation(s)

1 Department of Planning Management, Expresspay Card Co., Ltd, No.23, Zhongshan East 1st Rd., Huangpu District, Shanghai, China
2 Department of Strategic Development, Ningbo Citizen Card Operation Co., Ltd., 12F, Block A, Hebang Building, No933, North Tiantong Road, Ningbo, China

Corresponding Author

Yuhang Bi

ABSTRACT

Evolutionary multi-objective optimization (EMO) algorithm is a new multi-objective optimization algorithm developed in recent years, which has a broad application prospect in dealing with multi-objective optimization problems. This paper recognizes some recent efforts and discusses some feasible directions to develop potential EMO algorithms for solving high-dimensional objective optimization problems. A many-objective evolutionary strategy based on angle dominance (MaOES-AD) is proposed. The proposed MaOES -AD is applied to a many-objective test problem with multiple objectives and compared with recently proposed algorithms. It is proved that the proposed MaOES-AD algorithm achieves satisfactory results on all the considered problems.

KEYWORDS

Evolutionary multi-objective optimization, many-objective optimization problems, angle dominance, large dimension

CITE THIS PAPER

Yuhang Bi, Qinghua Zhao, A Many-Objective Evolutionary Strategy Based on Angle Dominance. Advances in Computer, Signals and Systems (2023) Vol. 7: 1-11. DOI: http://dx.doi.org/10.23977/acss.2023.070101.

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