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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 7
1980-1983

Backtracking search optimization algorithm based on mutation and crossing equations and evolutionary selection mechanism

Zhao Linjing1a,1b
Ge Baozhen1a,1b
Chen Lei1a,1b,2
1. a. School of Precision Instruments & Opto-Electronics Engineering, b. Key Laboratory of Opto-Electronics Information & Technical Science for Ministry of Education, Tianjin University, Tianjin 300072, China
2. School of Information Engineering, Tianjin University of Commerce, Tianjin 300134, China
DOI: 10.19734/j.issn.1001-3695.2017.12.0848

Abstract

According to the slow convergence and easiness to trap in local optimum of backtracking search optimization algorithm, this paper presented an improved algorithm. The method proposed a mutation scale factor based on t distribution firstly to speed up the convergence rate. Then the algorithm improved the structure of crossover equation and introduced the optimal individual to control the direction of population search, which effectively improved the development capability. Finally, the algorithm proposed the evolutionary selection mechanism, introduced the mutation factor of differential evolution algorithm and replaced the optimal solution with worse solution under a certain probability, which can avoid algorithm to fall into the local optimum. The numerical experiments selected 15 test functions for simulation and compared with 5 well-behaved algorithms. The results show that the proposed algorithm has obvious advantages in terms of convergence rate and search accuracy.

Foundation Support

国家自然科学基金重点资助项目(61535008)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2017.12.0848
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 7
Section: Algorithm Research & Explore
Pages: 1980-1983
Serial Number: 1001-3695(2019)07-013-1980-04

Publish History

[2019-07-05] Printed Article

Cite This Article

赵琳敬, 葛宝臻, 陈雷. 基于变异交叉方程与进化选择机制的回溯优化改进算法 [J]. 计算机应用研究, 2019, 36 (7): 1980-1983. (Zhao Linjing, Ge Baozhen, Chen Lei. Backtracking search optimization algorithm based on mutation and crossing equations and evolutionary selection mechanism [J]. Application Research of Computers, 2019, 36 (7): 1980-1983. )

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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