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浙江大学学报(理学版)  2018, Vol. 45 Issue (3): 272-283    DOI: 10.3785/j.issn.1008-9497.2018.03.002
现代优化理论与算法专栏     
耗散结构和差分变异混合的鸡群算法
韩萌
西安电子科技大学 数学与统计学院, 陕西 西安 710126
Hybrid chicken swarm algorithm with dissipative structure and differential mutation
HAN Meng
School of Mathematics and Statistics, Xidian University, Xi'an 710126, China
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摘要: 针对标准鸡群算法在求解高维优化问题时过早收敛于局部最优和收敛速度慢等问题,提出了一种耗散结构和差分变异混合的鸡群算法.该算法通过将耗散结构引入至雄鸡位置的更新公式,扩大了鸡群的搜索空间,增强了算法的全局搜索能力;同时,通过对随机选择的个体进行差分变异操作,增强了算法的收敛性能.对选取的18个标准函数进行仿真实验,结果表明,算法的收敛精度、收敛速度和稳定性均明显优于其他几种算法.
关键词: 鸡群算法耗散结构差分变异高维优化问题    
Abstract: To overcome the drawbacks that the chicken swarm algorithm is liable to fall into the local optimum and is slow when solving the high-dimension problems, this paper proposes a hybrid chicken swarm algorithm with dissipative structure and differential mutation. A dissipative structure is adapted in cock position to enlarge the search space of the whole flock, so as to enhance the global searching ability. Meanwhile, differential mutation is applied in some randomly selected individuals to improve the convergence of the chicken swarm algorithm. Numerical experiments conducted on the 18 classical test functions that the proposed algorithm is superior to other algorithms.
Key words: chicken swarm algorithm    dissipative structure    differential mutation    high-dimensional optimization problem
收稿日期: 2017-08-24 出版日期: 2018-03-15
CLC:  TP18  
基金资助: 国家自然科学基金资助项目(61373174).
作者简介: 韩萌(1993-),ORCID:http://orcid.org/0000-0002-4176-9014,女,硕士,主要从事智能优化算法、最优化理论及其应用研究,E-mail:meng_10110826@163.com.
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引用本文:

韩萌. 耗散结构和差分变异混合的鸡群算法[J]. 浙江大学学报(理学版), 2018, 45(3): 272-283.

HAN Meng. Hybrid chicken swarm algorithm with dissipative structure and differential mutation. Journal of Zhejiang University (Science Edition), 2018, 45(3): 272-283.

链接本文:

https://www.zjujournals.com/sci/CN/10.3785/j.issn.1008-9497.2018.03.002        https://www.zjujournals.com/sci/CN/Y2018/V45/I3/272

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