Cuckoo Search Algorithm with Hybrid Factor Using Dimensional Distance

被引:1
|
作者
Lin, Yaohua [1 ]
Zhang, Cuiping [2 ]
Liang, Zhong [1 ]
机构
[1] Fujian Agr & Forestry Univ, Coll Comp & Informat Sci, Fuzhou 350002, Peoples R China
[2] Fujian Univ Tradit Chinese Med, Coll Management, Fuzhou 350002, Peoples R China
关键词
OPTIMIZATION;
D O I
10.1155/2016/4839763
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper proposes a hybrid factor strategy for cuckoo search algorithm by combining constant factor and varied factor. The constant factor is used to the dimensions of each solution which are closer to the corresponding dimensions of the best solution, while the varied factor using a randomor a chaotic sequence is utilized to farer dimensions. For each solution, the dimension whose distance to the corresponding one of the best solution is shorter than mean distance of all dimensional distances will be regarded as the closer one, otherwise as the farer one. A suit of 20 benchmark functions are employed to verify the performance of the proposed strategy, and the results show the improvement in effectiveness and efficiency of the hybridization.
引用
收藏
页数:11
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