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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 8
2404-2411

Multi-objective wolf pack algorithm with elite guidance and information interaction

Chen Fujun1a,1b
Wu Runxiu1a,1b
Xiao Renbin2
Wang Hui1a,1b
Zhao Jia1a,1b
1. a. School of Information Engineering, b. Nanchang Key Laboratory of IoT Perception & Collaborative Computing for Smart City, Nanchang Institute of Technology, Nanchang 330099, China
2. School of Artificial Intelligence & Automation, Huazhong University of Science & Techno-logy, Wuhan 430074, China
DOI: 10.19734/j.issn.1001-3695.2023.12.0587

Abstract

In consideration of the superior performance of the wolf pack algorithm on single-objective optimization problems, combining with the biological habits of wolves to apply it to multi-objective optimization problems, this paper proposed a multi-objective wolf pack algorithm with elite guidance and information interaction(MOWPA-EGII). Firstly, MOWPA-EGII proposed an elite guidance strategy, using the elite wolf in the external file and the head wolf of the current sub-population to jointly guide the population movement, so that the artificial wolves uniformly distributed in the whole search space, and the strategy enhanced the global search ability of the algorithm; Secondly, it designed the information interaction mechanism to simulate the information transfer in the wolf hunting process, so that individuals with different advantages could transfer information to each other to ensure the hunting efficiency of the wolves and improved the ability of the algorithm to explore the optimal solution of the Pareto; Finally, it added the mutation operator to perturb the moving direction of the artificial wolves, so as to let the algorithm jump out of the local optimum and enhance the local search ability of the algorithm. In order to verify the effectiveness of MOWPA-EGII, comparing it with 5 classical algorithms and 10 recent algorithms, and the results show that MOWPA-EGII possesses good convergence and diversity, which proves that the present algorithm has a better optimization performance.

Foundation Support

国家自然科学基金资助项目(52069014)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.12.0587
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 8
Section: Algorithm Research & Explore
Pages: 2404-2411
Serial Number: 1001-3695(2024)08-022-2404-08

Publish History

[2024-04-08] Accepted Paper
[2024-08-05] Printed Article

Cite This Article

陈福军, 吴润秀, 肖人彬, 等. 精英引导和信息交互的多目标狼群算法 [J]. 计算机应用研究, 2024, 41 (8): 2404-2411. (Chen Fujun, Wu Runxiu, Xiao Renbin, et al. Multi-objective wolf pack algorithm with elite guidance and information interaction [J]. Application Research of Computers, 2024, 41 (8): 2404-2411. )

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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