Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 3
721-728,763

Hybrid optimization algorithm for salp swarm and butterfly with reverse mutation towards optimization learning

Huang Xinyu
Ma Ning
Fu Wei
Ji Weidong
Qi Wenfeng
School of Computer Science & Information Engineering, Harbin Normal University, Harbin 150025, China
DOI: 10.19734/j.issn.1001-3695.2023.07.0328

Abstract

To address the problems of the butterfly optimization algorithm, such as include vulnerability to local optima, low optimization accuracy and slow convergence speed, this paper proposed a hybrid optimization algorithm for salp swarm and butterfly with reverse mutation towards optimization learning. The algorithm introduced Cauchy mutation to disturb the optimal butterfly individual to avoid the algorithm falling into local optimization. Embedding the improved salp swarm algorithm(SSA) into BOA, it adjusted the proportion of global exploration and local mining, thereby enhancing the algorithm's convergence speed. Using the reverse mutation towards optimization learning strategy, it enhanced the algorithm's search space and improved the quality of solutions, consequently bolstering its overall optimization accuracy. The experimental results obtained from conducting simulations on 10 benchmark functions, show the exceptional optimization performance and robustness of the improved algorithm.

Foundation Support

黑龙江省自然科学基金资助项目(LH2021F037)
黑龙江省高等教育教学改革资助项目(SJGY20180259)
哈尔滨市科技局科技创新人才研究专项资助项目(2017RAQXJ050)
哈尔滨师范大学博士科研启动基金资助项目(XKB201901)
哈尔滨师范大学计算机学院科研资助项目(JKYKYY202006)
哈尔滨师范大学研究生培养质量提升工程资助项目(HSDYJSJG2019006)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.07.0328
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 3
Section: Algorithm Research & Explore
Pages: 721-728,763
Serial Number: 1001-3695(2024)03-012-0721-08

Publish History

[2023-11-01] Accepted Paper
[2024-03-05] Printed Article

Cite This Article

黄鑫宇, 马宁, 付伟, 等. 趋优变异反向学习的樽海鞘群与蝴蝶混合优化算法 [J]. 计算机应用研究, 2024, 41 (3): 721-728,763. (Huang Xinyu, Ma Ning, Fu Wei, et al. Hybrid optimization algorithm for salp swarm and butterfly with reverse mutation towards optimization learning [J]. Application Research of Computers, 2024, 41 (3): 721-728,763. )

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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