计算机科学 ›› 2014, Vol. 41 ›› Issue (7): 279-282.doi: 10.11896/j.issn.1002-137X.2014.07.058

• 人工智能 • 上一篇    下一篇

一种新的自适应布谷鸟搜索算法

钱伟懿,候慧超,姜守勇   

  1. 渤海大学数理学院 锦州121000;渤海大学数理学院 锦州121000;东北大学信息科学与工程学院 沈阳110819
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受国家自然科学基金项目(11371071),辽宁省自然基金项目(20102003),辽宁省教育厅科学研究项目(L2013426)资助

New Self-adaptive Cuckoo Search Algorithm

QIAN Wei-yi,HOU Hui-chao and JIANG Shou-yong   

  • Online:2018-11-14 Published:2018-11-14

摘要: 为提高布谷鸟搜索(cuckoo search)算法(CS)的局部与全局搜索能力和收敛速度,提出了一种新的自适应布谷鸟算法。在该算法中,提出一种自适应参数控制策略来动态地调整CS中的步长因子,以增强CS的搜索性能。另外,把类似差分进化算法变异策略引入到CS中,以进一步提高CS的种群多样性。仿真实验表明,改进的CS算法的优化性能得到了明显改善。

关键词: 布谷鸟搜索算法,莱维飞行,自适应,变异 中图法分类号TP18文献标识码A

Abstract: In order to improve the local and global search ability of cuckoo search algorithm(CS) and its convergence rate,a new self-adaptive cuckoo search algorithm was proposed.In this algorithm,a self-adaptive parameter control strategy is used to adjust the step size of CS,thereby enhancing the search ability of CS.In addition,a mutation technique which is similar to differential evolution algorithm is utilized to guarantee the CS diversity.Experimental results show that the proposed algorithm is much more effective.

Key words: Cuckoo search algorithm,Levy flight,Self-adaptation,Mutation

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