Journal of Hebei University(Natural Science Edition) >

2019 , Vol. 39 >Issue 1: 86 - 92

DOI: https://doi.org/10.3969/j.issn.1000-1565.2019.01.015

Improvement and parallelism of real-coded genetic algorithm

  • LIU Zhenpeng ,
  • WANG Xuefeng ,
  • XUE Lei ,
  • ZHANG Bin ,
  • ZHANG Shouhua
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  • 1. School of Cyberspace Security and Computer, Hebei University, Baoding 071002, China; 2. Information Technology Center, Hebei University, Baoding 071002, China

Received date: 2018-09-06

  Online published: 2019-01-25

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Abstract

Aiming at the shortcoming of the real-coded genetic algorithm, which is easy to fall into local extremum and slow convergence speed, an improved real-coded genetic algorithm is proposed and implemented by GPU-based parallelization. Through four typical genetic algorithm performance test functions, the results show that the improved algorithm can not only effectively jump out of the local extremum, but also accelerate the convergence speed of the algorithm; When solving complex high-dimensional functions, the improved parallel algorithm can significantly reduce the running time of the algorithm.

Key words： genetic algorithm; real-coded; algorithm improvement; GPU parallel

Cite this article

LIU Zhenpeng , WANG Xuefeng , XUE Lei , ZHANG Bin , ZHANG Shouhua . Improvement and parallelism of real-coded genetic algorithm[J]. Journal of Hebei University(Natural Science Edition), 2019 , 39(1) : 86 -92 . DOI: 10.3969/j.issn.1000-1565.2019.01.015

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