Evolutionary programming based on non-uniform mutation

被引:77
|
作者
Zhao, Xinchao [1 ,2 ]
Gao, Xiao-Shan [2 ]
Hu, Ze-Chun [3 ]
机构
[1] Beijing Univ Posts & Telecommun, Sch Sci, Beijing 100876, Peoples R China
[2] Acad Sinica, AMSS, Inst Syst Sci, KLMM, Beijing 100080, Peoples R China
[3] Nanjing Univ, Dept Math, Nanjing 210093, Peoples R China
基金
美国国家科学基金会;
关键词
evolutionary programming; non-uniform mutation; executing process;
D O I
10.1016/j.amc.2006.06.107
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
A new evolutionary programming using non-uniform mutation instead of Gaussian, Cauchy and Levy mutations is proposed. Evolutionary programming with non-uniform mutation (NEP) has the merits of searching the space uniformly at the early stage and very locally at the later stage during the programming. For a suite of 14 benchmark problems, NEP outperforms the improved evolutionary programming using mutation based on Levy probability distribution (ILEP) for multimodal functions with many local minima while being comparable to ILEP in performance for unimodal and multimodal functions with only a few minima. The detailed theoretical analysis of the executing process of NEP and the expected step size on non-uniform mutation are given. (c) 2006 Elsevier Inc. All rights reserved.
引用
收藏
页码:1 / 11
页数:11
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