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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 12
3618-3621

Improved whale optimization algorithm

Wu Zequana
Mu Yongminb
a. Beijing Key Laboratory of Internet Culture & Digital Dissemination Research, b. School of Computer Science, Beijing Information Science & Technology University, Beijing 100101, China
DOI: 10.19734/j.issn.1001-3695.2019.09.0536

Abstract

Aiming at the problem that the WOA was easy to fall into local optimum and low convergence precision, this paper proposed an improved whale optimization algorithm(IWOA). The algorithm initialized the population by quasi-reverse lear-ning methods and improved the diversity of the population. Then the algorithm modified the linear convergence factor to a nonlinear convergence factor, which was beneficial to balance the global search ability and local development ability. In addition, the algorithm improved the local search ability of the whale optimization algorithm by increasing the adaptive weight and improved convergence precision. Finally, the algorithm adjusted the whale optimization algorithm in time by a random differential mutation strategy to avoid falling into the local optimum. It selected nine benchmark functions in the experiment, and iterated all the algorithms 30 times. The improved whale optimization algorithm compared to the original whale optimization algorithm and five improved whale optimization algorithms, the results show that the mean and standard deviation of the algorithm are better than other algorithms, the convergence curve of the algorithm is also superior to most other algorithms. It shows that the improved whale optimization algorithm has the best convergence accuracy and algorithm stability, and the convergence speed is significantly faster than most other improved whale optimization algorithms.

Foundation Support

北京市自然科学基金资助项目(Z160002)
网络文化与数字传播北京市重点实验室开放课题资助项目(5221935409)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.09.0536
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 12
Section: Algorithm Research & Explore
Pages: 3618-3621
Serial Number: 1001-3695(2020)12-020-3618-04

Publish History

[2020-12-05] Printed Article

Cite This Article

武泽权, 牟永敏. 一种改进的鲸鱼优化算法 [J]. 计算机应用研究, 2020, 37 (12): 3618-3621. (Wu Zequan, Mu Yongmin. Improved whale optimization algorithm [J]. Application Research of Computers, 2020, 37 (12): 3618-3621. )

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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