Algorithm Research & Explore
|
367-373,378

Improved biogeography-based optimization algorithm introducing species evolution

Zhang Qiwen
Yang Yongchao
School of Computer & Communication, Lanzhou University of Technology, Lanzhou 730050, China

Abstract

In order to solve the problem of premature convergence and falling into local optimum in biogeography-based optimization algorithm, this paper proposed an improved biogeography-based optimization algorithm introducing species evolution(SEBBO). The algorithm divided all habitats into three regions according to the number of species, established a co-evolution relationship, and reasonably adopted interval invasion and regional cooperation/competition strategies to meet diversity while avoided premature convergence. It defined two mutation strategies of species change and species development, and designed the dual-strategy cooperative mutation operator to solve the damage of the mutation operator to the better solution. Then, compared with standard BBO and other related improved algorithms on 8 benchmark functions from CEC2017, SEBBO algorithm is superior to BBO and other BBO variants in terms of algorithm performance and stability, and local optimal values is not easily limit the algorithm. Finally, this paper applied the SEBBO algorithm to flexible Job-Shop scheduling with maximum completion time as the goal to test its practical application value. Experiments show that the algorithm has a certain effectiveness in solving FJSP.

Foundation Support

国家自然科学基金资助项目(62063021)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.08.0316
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 2
Section: Algorithm Research & Explore
Pages: 367-373,378
Serial Number: 1001-3695(2022)02-007-0367-07

Publish History

[2021-11-13] Accepted Paper
[2022-02-05] Printed Article

Cite This Article

张其文, 杨勇超. 引入物种演化的改进生物地理学优化算法 [J]. 计算机应用研究, 2022, 39 (2): 367-373,378. (Zhang Qiwen, Yang Yongchao. Improved biogeography-based optimization algorithm introducing species evolution [J]. Application Research of Computers, 2022, 39 (2): 367-373,378. )

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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