In accordance with regulations and requirements, the editorial department's website domain has been changed to arocmag.cn. The original domain (arocmag.com) will be discontinued after Dec. 31st, 2024.
See More
Algorithm Research & Explore
|
App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 3
696-703,724

Salp swarm algorithm combining information feedback sharing and mayfly search mechanism

Li Kewen
Geng Wenliang
Zhang Min
Wang Xiaohui
Ke Cuihong
College of Computer Science & Technology, China University of Petroleum(East China), Qingdao Shandong 266580, China
DOI: 10.19734/j.issn.1001-3695.2022.07.0363

Abstract

Aiming at the problems of slow convergence speed and easy to fall into local optimum of SSA, this paper proposed an improved salp swarm algorithm combing information feedback sharing and mayfly search mechanism. Firstly, it used piecewise chaos to initialize the population to make the initial salps more evenly cover the feasible space. It adopted the information sharing mechanism to propose an auxiliary leader strategy, in order to improve the leader position update formula, and enhance the global search ability. It used the evolutionary theory and the idea of positive and negative feedback regulation, selecting better leaders through mutation operation and natural selection, so as to improve the search ability precision. Finally, it put forward the mayfly search mechanism, selected the mating formula of the mayfly algorithm to optimize the iterative formula of the follower position and make the algorithm converge faster in the later stage. Experiments on 12 benchmark functions and 17 CEC test functions prove the comprehensive performance of the improved salp population algorithm, and the ablation experiments verifiy the effectiveness of the improved strategy. The experimental results show that the improved algorithm has obvious advantages in convergence speed and search accuracy.

Foundation Support

国家自然科学基金重大项目(51991365)
山东省自然科学基金资助项目(ZR2021MF082)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.07.0363
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 3
Section: Algorithm Research & Explore
Pages: 696-703,724
Serial Number: 1001-3695(2023)03-009-0696-08

Publish History

[2022-10-14] Accepted Paper
[2023-03-05] Printed Article

Cite This Article

李克文, 耿文亮, 张敏, 等. 融合信息反馈共享与蜉蝣搜索机制的樽海鞘群算法 [J]. 计算机应用研究, 2023, 40 (3): 696-703,724. (Li Kewen, Geng Wenliang, Zhang Min, et al. Salp swarm algorithm combining information feedback sharing and mayfly search mechanism [J]. Application Research of Computers, 2023, 40 (3): 696-703,724. )

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)