Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 9
2674-2680

Whale optimization algorithm based on multi-dimensional variation learning and distributed optimization

Guan Yanpeng
Li Ziming
Jia Xinchun
School of Automation & Software Engineering, Shanxi University, Taiyuan 030031, China
DOI: 10.19734/j.issn.1001-3695.2023.02.0049

Abstract

Aiming at the shortcomings of low convergence accuracy and easy to be captured by local optimum when whale optimization algorithm(WOA) solved problems such as high dimension, multi-peak and non-origin of optimal value, this paper proposed a whale optimization algorithm based on multi-dimensional variation learning and distributed optimization(MLDOWOA). Firstly, this algorithm introduced adaptive weights and dominant individual interference to dynamically adjust the direction of individual spiral surround, which improved the global search ability and convergence accuracy of the algorithm. Then, in order to further expand the search range of the algorithm, it used a multi-dimensional variation learning mechanism to adaptively plan the direction of population variation. Finally, it put forward the distributed optimization mechanism to coordinate the step size of search, so as to help the population break through the limitation of search stagnation in the middle and late stage. The test results on 8 high dimensional benchmark functions and 4 fixed dimensional benchmark functions show that, compared with the basic WOA, SSA and the improved ACWOA, AWOA, MSIWOA, ADWOA, the MLDOWOA has significant advantages in convergence accuracy and ability to cope with high dimensional functions. This paper used the MLDOWOA to tune the parameters of the FOPID controller, and compared the control results with the research results of this engineering problem in recent years. It proves the excellent performance of the proposed algorithm in FOPID parameter tuning problems.

Foundation Support

国家自然科学基金资助项目(61973201)
山西省科技厅资助项目(202103021224030)
山西省省筹资金资助回国留学人员科研项目(2022-009)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.02.0049
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 9
Section: Algorithm Research & Explore
Pages: 2674-2680
Serial Number: 1001-3695(2023)09-018-2674-07

Publish History

[2023-04-26] Accepted Paper
[2023-09-05] Printed Article

Cite This Article

关燕鹏, 李子鸣, 贾新春. 基于多维度变异学习与收散归优的鲸鱼优化算法 [J]. 计算机应用研究, 2023, 40 (9): 2674-2680. (Guan Yanpeng, Li Ziming, Jia Xinchun. Whale optimization algorithm based on multi-dimensional variation learning and distributed optimization [J]. Application Research of Computers, 2023, 40 (9): 2674-2680. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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