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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 5
1409-1419

Grey wolf optimization algorithm based on progressive grouping hunting mechanism and its engineering applications

Yuan Yutinga,b
Gao Yuelinb,c
Zuo Wenlub,c
a. School of Computer Science & Engineering, b. Ningxia Collaborative Innovation Center for Scientific Computing and Intelligent Information Processing, c. School of Mathematics & Information Science, North Minzu University, Yinchuan 750021, China
DOI: 10.19734/j.issn.1001-3695.2023.10.0449

Abstract

Focus on the shortcomings of the GWO in solving complex optimization problems, such as slow convergence speed and easy to fall into local optimum, this paper proposed a grey wolf optimization algorithm based on progressive grouping hunting mechanism(PGGWO). Firstly, it designed the nonlinear multi convergence factors to enhance the global exploration ability and avoid local optimum. Secondly, it proposed a progressive location update strategy. The strategy introduced the encirclement strategy of coati and dynamic weight factors, the former avoided local optimum while improving convergence accuracy and speed, the latter dynamically improved the convergence speed and global optimization performance of the algorithm. Finally, through comparing with GWO, 4 advanced GWO variants and 4 new with strong competitiveness, the experiment verifies the effectiveness and advancement of PGGWO. The experimental results on 24 Benchmark functions and 3 practical engineering optimization problems show that PGGWO has obvious advantages in convergence accuracy and convergence speed, and is also effective for constrained optimization problems.

Foundation Support

宁夏自然科学基金重点资助项目(2022AAC02043)
宁夏高等学校一流学科建设基金资助项目(NXYLXK2017B09)
北方民族大学重大专项(ZDZX201901)
南京证券支持基础学科研究项目(NJZQJCXK202201)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.10.0449
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 5
Section: Algorithm Research & Explore
Pages: 1409-1419
Serial Number: 1001-3695(2024)05-019-1409-11

Publish History

[2024-01-16] Accepted Paper
[2024-05-05] Printed Article

Cite This Article

袁钰婷, 高岳林, 左汶鹭. 渐进式分组狩猎的灰狼优化算法及其工程应用 [J]. 计算机应用研究, 2024, 41 (5): 1409-1419. (Yuan Yuting, Gao Yuelin, Zuo Wenlu. Grey wolf optimization algorithm based on progressive grouping hunting mechanism and its engineering applications [J]. Application Research of Computers, 2024, 41 (5): 1409-1419. )

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.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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