Improved Differential Evolutionary Algorithm Based on Adaptive Scaling Factor

Chen Zhang; Haotian Li; Yifei Yang; Baohang Zhang; Huisheng Zhu; Shangce Gao

doi:10.1007/978-3-031-36822-6_15

Improved Differential Evolutionary Algorithm Based on Adaptive Scaling Factor

Chen Zhang, Haotian Li, Yifei Yang, Baohang Zhang, Huisheng Zhu, Shangce Gao^*

^*Corresponding author for this work

Intellectual Information Engineering

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

Abstract

The differential evolution algorithm is a meta-heuristic algorithm with the advantages of a simple structure, few control parameters, and robustness. However, in the face of different problems, if the factor F controlling the difference amplification is fixed, it will be difficult for the algorithm to adapt to complex and changeable problems. In order to enable the differential evolution algorithm to deal with many problems with the optimal F parameter, this paper proposes a differential evolution algorithm with Adaptive Scaling Factor. The algorithm continuously explores the optimal F parameters for the current problem while ensuring that it does not converge prematurely, which eventually leads to an improvement in the search efficiency of the algorithm.

Original language	English
Title of host publication	Advances and Trends in Artificial Intelligence. Theory and Applications - 36th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2023, Proceedings, Part II
Editors	Hamido Fujita, Yinglin Wang, Yanghua Xiao, Ali Moonis
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	171-176
Number of pages	6
ISBN (Print)	9783031368219
DOIs	https://doi.org/10.1007/978-3-031-36822-6_15
State	Published - 2023
Event	36th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2023 - Shanghai, China Duration: 2023/07/19 → 2023/07/22

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13926 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	36th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2023
Country/Territory	China
City	Shanghai
Period	2023/07/19 → 2023/07/22

Keywords

Adaptive Scaling Factor
Differential Evolution Algorithm
Meta-heuristic Algorithm

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-031-36822-6_15

Cite this

Zhang, C., Li, H., Yang, Y., Zhang, B., Zhu, H., & Gao, S. (2023). Improved Differential Evolutionary Algorithm Based on Adaptive Scaling Factor. In H. Fujita, Y. Wang, Y. Xiao, & A. Moonis (Eds.), Advances and Trends in Artificial Intelligence. Theory and Applications - 36th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2023, Proceedings, Part II (pp. 171-176). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13926 LNAI). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-36822-6_15

Zhang, Chen ; Li, Haotian ; Yang, Yifei et al. / Improved Differential Evolutionary Algorithm Based on Adaptive Scaling Factor. Advances and Trends in Artificial Intelligence. Theory and Applications - 36th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2023, Proceedings, Part II. editor / Hamido Fujita ; Yinglin Wang ; Yanghua Xiao ; Ali Moonis. Springer Science and Business Media Deutschland GmbH, 2023. pp. 171-176 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Improved Differential Evolutionary Algorithm Based on Adaptive Scaling Factor",

abstract = "The differential evolution algorithm is a meta-heuristic algorithm with the advantages of a simple structure, few control parameters, and robustness. However, in the face of different problems, if the factor F controlling the difference amplification is fixed, it will be difficult for the algorithm to adapt to complex and changeable problems. In order to enable the differential evolution algorithm to deal with many problems with the optimal F parameter, this paper proposes a differential evolution algorithm with Adaptive Scaling Factor. The algorithm continuously explores the optimal F parameters for the current problem while ensuring that it does not converge prematurely, which eventually leads to an improvement in the search efficiency of the algorithm.",

keywords = "Adaptive Scaling Factor, Differential Evolution Algorithm, Meta-heuristic Algorithm",

author = "Chen Zhang and Haotian Li and Yifei Yang and Baohang Zhang and Huisheng Zhu and Shangce Gao",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 36th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2023 ; Conference date: 19-07-2023 Through 22-07-2023",

year = "2023",

doi = "10.1007/978-3-031-36822-6_15",

language = "英語",

isbn = "9783031368219",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "171--176",

editor = "Hamido Fujita and Yinglin Wang and Yanghua Xiao and Ali Moonis",

booktitle = "Advances and Trends in Artificial Intelligence. Theory and Applications - 36th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2023, Proceedings, Part II",

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Zhang, C, Li, H, Yang, Y, Zhang, B, Zhu, H & Gao, S 2023, Improved Differential Evolutionary Algorithm Based on Adaptive Scaling Factor. in H Fujita, Y Wang, Y Xiao & A Moonis (eds), Advances and Trends in Artificial Intelligence. Theory and Applications - 36th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2023, Proceedings, Part II. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13926 LNAI, Springer Science and Business Media Deutschland GmbH, pp. 171-176, 36th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2023, Shanghai, China, 2023/07/19. https://doi.org/10.1007/978-3-031-36822-6_15

Improved Differential Evolutionary Algorithm Based on Adaptive Scaling Factor. / Zhang, Chen; Li, Haotian; Yang, Yifei et al.
Advances and Trends in Artificial Intelligence. Theory and Applications - 36th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2023, Proceedings, Part II. ed. / Hamido Fujita; Yinglin Wang; Yanghua Xiao; Ali Moonis. Springer Science and Business Media Deutschland GmbH, 2023. p. 171-176 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13926 LNAI).

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

TY - GEN

T1 - Improved Differential Evolutionary Algorithm Based on Adaptive Scaling Factor

AU - Zhang, Chen

AU - Li, Haotian

AU - Yang, Yifei

AU - Zhang, Baohang

AU - Zhu, Huisheng

AU - Gao, Shangce

PY - 2023

Y1 - 2023

N2 - The differential evolution algorithm is a meta-heuristic algorithm with the advantages of a simple structure, few control parameters, and robustness. However, in the face of different problems, if the factor F controlling the difference amplification is fixed, it will be difficult for the algorithm to adapt to complex and changeable problems. In order to enable the differential evolution algorithm to deal with many problems with the optimal F parameter, this paper proposes a differential evolution algorithm with Adaptive Scaling Factor. The algorithm continuously explores the optimal F parameters for the current problem while ensuring that it does not converge prematurely, which eventually leads to an improvement in the search efficiency of the algorithm.

AB - The differential evolution algorithm is a meta-heuristic algorithm with the advantages of a simple structure, few control parameters, and robustness. However, in the face of different problems, if the factor F controlling the difference amplification is fixed, it will be difficult for the algorithm to adapt to complex and changeable problems. In order to enable the differential evolution algorithm to deal with many problems with the optimal F parameter, this paper proposes a differential evolution algorithm with Adaptive Scaling Factor. The algorithm continuously explores the optimal F parameters for the current problem while ensuring that it does not converge prematurely, which eventually leads to an improvement in the search efficiency of the algorithm.

KW - Adaptive Scaling Factor

KW - Differential Evolution Algorithm

KW - Meta-heuristic Algorithm

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BT - Advances and Trends in Artificial Intelligence. Theory and Applications - 36th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2023, Proceedings, Part II

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T2 - 36th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2023

Y2 - 19 July 2023 through 22 July 2023

ER -

Zhang C, Li H, Yang Y, Zhang B, Zhu H, Gao S. Improved Differential Evolutionary Algorithm Based on Adaptive Scaling Factor. In Fujita H, Wang Y, Xiao Y, Moonis A, editors, Advances and Trends in Artificial Intelligence. Theory and Applications - 36th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2023, Proceedings, Part II. Springer Science and Business Media Deutschland GmbH. 2023. p. 171-176. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-36822-6_15

Improved Differential Evolutionary Algorithm Based on Adaptive Scaling Factor

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