Algorithm Research & Explore
|
App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 3
736-745,771

Improved honey badger algorithm for dual population collaborative evolution

Chai Yan
Wang Ruxin
Ren Sheng
College of Science, Liaoning Technical University, Fuxin Liaoning 125105, China
DOI: 10.19734/j.issn.1001-3695.2023.05.0293

Abstract

To address the weaknesses of the honey badger algorithm, specifically its limited capacity for local search and susceptibility to local optima, this paper proposed an enhanced version based on coevolution with two populations. This approach used Cubic chaotic mapping to initialize the population, thereby expanding the search space and improving its distribution. Moreover, it introduced a dual-population optimization mechanism that combined the slime mold algorithm with the honey badger algorithm. By leveraging the strengths of both methods, the individuals could more effectively hone-in on the target location, resulting in improved search efficiency and optimization performance. To further improve the algorithm's ability to escape local optima, it employed a Cauchy random reverse perturbation strategy to disturb the optimal position of the honey badger population. By means of the experiment of improving the effectiveness of a single strategy, different high-dimensional experiments with seven other algorithms and Wilcoxon rank-sum tests, experimental results demonstrate that the proposed algorithm has high convergence accuracy and fast solving times. Finally, this paper applied the improved algorithm to the design of compression springs and pressure vessels, which further confirmed the efficacy of improved strategy and the practical utility of the algorithm.

Foundation Support

教育部规划基金青年项目(21YJCZH204)
辽宁省自然科学基金资助项目(2020-MS-301)
辽宁省教育厅资助项目(LJKMZ20220694)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.05.0293
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 3
Section: Algorithm Research & Explore
Pages: 736-745,771
Serial Number: 1001-3695(2024)03-014-0736-10

Publish History

[2023-09-06] Accepted Paper
[2024-03-05] Printed Article

Cite This Article

柴岩, 王如新, 任生. 双种群协同演化的改进蜜獾算法 [J]. 计算机应用研究, 2024, 41 (3): 736-745,771. (Chai Yan, Wang Ruxin, Ren Sheng. Improved honey badger algorithm for dual population collaborative evolution [J]. Application Research of Computers, 2024, 41 (3): 736-745,771. )

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.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)