广东工业大学学报 ›› 2016, Vol. 33 ›› Issue (01): 57-61.doi: 10.3969/j.issn.1007-7162.2016.01.011

• 综合研究 • 上一篇    下一篇

自适应混沌变异的万有引力搜索算法

罗萍,刘伟,周述波   

  1. 广东工业大学 应用数学学院,广东 广州 510520
  • 收稿日期:2014-09-23 出版日期:2016-01-16 发布日期:2016-01-16
  • 作者简介:罗萍(1987-),女,硕士研究生,主要研究方向为智能计算及其应用.
  • 基金资助:

    国家自然科学基金资助项目(60974077)

Gravitational Search Algorithm of Adaptive Chaos Mutation

Luo Ping, Liu Wei, Zhou Shu-bo   

  1. School of Applied Mathematics, Guangdong University of Technology, Guangzhou 510520, China
  • Received:2014-09-23 Online:2016-01-16 Published:2016-01-16

摘要: 通过引入平均粒距和混沌搜索变异,提高万有引力算法的局部搜索能力,增加物质种群的多样性.并且对变异后不可行的物质采用边界变异约束处理.实验结果表明,新算法收敛精度较高,收敛速度较快,能比较有效地避免早熟收敛问题.

关键词: 万有引力算法; 混沌; 平均粒距; 边界变异

Abstract: This paper proposes a gravitational search algorithm of adaptive chaos mutation. By introducing the average distance and the chaotic search variation, this paper improves local search ability of gravity algorithm, increases the diversity of substance population and treats the unfeasible materials after mutation by boundary variation constraint. The results show that the new algorithm has the advantages of high precision and fast rate in convergence which can effectively avoid premature convergence. And the variation of the material after not feasible material treated by boundary variationconstraint.

Key words: gravitational search algorithm; chaos; average particle distance; boundary mutation

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