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Algorithm Research & Explore
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134-140,145

Adaptive butterfly optimization algorithm based on mutation strategies

Liu Kai
Dai Yongqiang
College of Information Science & Technology, Gansu Agricultural University, Lanzhou 730070, China

Abstract

Butterfly optimization algorithm(BOA) is a novel nature-inspired metaheuristics algorithm proposed in recent years. The basic BOA is slow convergence, low accuracy and easy to fall into local optimum. To solve the above problem of basic BOA, this paper proposed an adaptive butterfly optimization algorithm based on mutation strategies(ABOA-MS). Firstly, it introduced the strategy of adjust the conversion probability dynamically, which effectively balanced the ability of the global exploration and local search, by means of dynamically adjusting the switching probability of the change information of iteration times and individual fitness. Secondly, it introduced the adaptive inertia weight strategy and local mutation strategy. It applied the inertia weight value and chaotic memory weight factor, which further improved the diversity of this algorithm, and effectively avoided its precocious convergence, as well as accelerated its convergence speed and solving accuracy. In order to verify the optimization performance of the modified algorithm, it carried out the simulation experiments among the modified algorithm, the basic BOA algorithm, the particle swarm optimization algorithm, the salp swarm algorithm, the gray wolf optimization and the others. Simulation results illustrate that the modified algorithm has excellent performance of fast convergence speed, high optimization accuracy and strong stability.

Foundation Support

甘肃农业大学青年导师基金资助项目(GAU-QDFC-2019-02)
甘肃省高等学校创新能力提升项目(2019A-056)
甘肃农业大学学科建设专项基金资助项目(GAU-XKJS-2018-253)
国家自然科学基金资助项目(61063028,61751313)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.06.0244
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 1
Section: Algorithm Research & Explore
Pages: 134-140,145
Serial Number: 1001-3695(2022)01-024-0134-07

Publish History

[2021-09-09] Accepted Paper
[2022-01-05] Printed Article

Cite This Article

刘凯, 代永强. 融合变异策略的自适应蝴蝶优化算法 [J]. 计算机应用研究, 2022, 39 (1): 134-140,145. (Liu Kai, Dai Yongqiang. Adaptive butterfly optimization algorithm based on mutation strategies [J]. Application Research of Computers, 2022, 39 (1): 134-140,145. )

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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