Improved strength Pareto evolutionary algorithm based on reference direction and coordinated selection strategy
In the field of evolutionary algorithms, Pareto‐based algorithms are less effective when more than three objectives are encountered, due to the lack of sufficient selection pressure. In this paper, a Pareto‐based many‐objective evolutionary algorithm with reference direction and coordinated selectio...
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| Vydáno v: | International journal of intelligent systems Ročník 36; číslo 9; s. 4693 - 4722 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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New York
John Wiley & Sons, Inc
01.09.2021
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| ISSN: | 0884-8173, 1098-111X |
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| Abstract | In the field of evolutionary algorithms, Pareto‐based algorithms are less effective when more than three objectives are encountered, due to the lack of sufficient selection pressure. In this paper, a Pareto‐based many‐objective evolutionary algorithm with reference direction and coordinated selection strategy, abbreviated as SPEACSS, is proposed. The algorithm inherits the fitness calculation strategy of the strength Pareto evolutionary algorithm, while it applied an efficient reference direction‐based density estimator and a novel selection strategy. Moreover, mating selection and environmental selection are complementary and coordinated in the evolutionary process and have better performance than be used alone. In the criteria of mating selection, a method is given to improve the effectiveness of the parent combination. Experimental results on benchmark functions show that the proposed algorithm is superior to several state‐of‐the‐art designs, and demonstrate the effectiveness of the improved algorithm in balancing diversity and convergence. |
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| AbstractList | In the field of evolutionary algorithms, Pareto‐based algorithms are less effective when more than three objectives are encountered, due to the lack of sufficient selection pressure. In this paper, a Pareto‐based many‐objective evolutionary algorithm with reference direction and coordinated selection strategy, abbreviated as SPEACSS, is proposed. The algorithm inherits the fitness calculation strategy of the strength Pareto evolutionary algorithm, while it applied an efficient reference direction‐based density estimator and a novel selection strategy. Moreover, mating selection and environmental selection are complementary and coordinated in the evolutionary process and have better performance than be used alone. In the criteria of mating selection, a method is given to improve the effectiveness of the parent combination. Experimental results on benchmark functions show that the proposed algorithm is superior to several state‐of‐the‐art designs, and demonstrate the effectiveness of the improved algorithm in balancing diversity and convergence. |
| Author | Xiong, Naixue Chen, Siqi Gu, Qinghua Jiang, Song |
| Author_xml | – sequence: 1 givenname: Qinghua orcidid: 0000-0003-4927-0653 surname: Gu fullname: Gu, Qinghua email: qinghuagu@126.com organization: Xi'an University of Architecture and Technology – sequence: 2 givenname: Siqi orcidid: 0000-0003-0218-4803 surname: Chen fullname: Chen, Siqi organization: Xi'an University of Architecture and Technology – sequence: 3 givenname: Song orcidid: 0000-0003-2151-0977 surname: Jiang fullname: Jiang, Song organization: Xi'an University of Architecture and Technology – sequence: 4 givenname: Naixue orcidid: 0000-0002-0394-4635 surname: Xiong fullname: Xiong, Naixue organization: Northeastern State University |
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| CitedBy_id | crossref_primary_10_1016_j_eswa_2022_119424 crossref_primary_10_3390_math10091564 crossref_primary_10_3390_su16041511 crossref_primary_10_1007_s10489_023_05106_1 crossref_primary_10_1016_j_asoc_2024_111967 crossref_primary_10_1007_s10489_024_05596_7 crossref_primary_10_1016_j_cherd_2023_03_022 crossref_primary_10_1080_0305215X_2023_2181343 crossref_primary_10_1002_int_22816 crossref_primary_10_3390_machines13030195 crossref_primary_10_1016_j_ins_2022_04_008 |
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| SubjectTerms | environment selection Evolutionary algorithms Genetic algorithms Intelligent systems many‐objective evolutionary algorithm Mathematical analysis mating selection strength Pareto evolutionary algorithm the cooperation of selection strategy |
| Title | Improved strength Pareto evolutionary algorithm based on reference direction and coordinated selection strategy |
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