A self-adaptive differential evolution algorithm for binary CSPs

被引：10
|
作者：
Fu, Hongjie [1 ,2 ]
Ouyang, Dantong [1 ]
Xu, Jiaming [3 ]
机构：
[1] Jilin Univ, Minist Educ, Key Lab Symbol Computat & Knowledge Engn, Changchun 130012, Peoples R China
[2] Coll Comp Sci & Technol, Jilin Teachers Inst Engn & Technol, Changchun 130052, Peoples R China
[3] China Internet Network Informat Ctr, Beijing 100000, Peoples R China
来源：
COMPUTERS & MATHEMATICS WITH APPLICATIONS | 2011年 / 62卷 / 07期
关键词：
Differential evolution; Self-adaptive; CSPs;
D O I：
10.1016/j.camwa.2011.06.053
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
A novel self-adaptive differential evolution (SADE) algorithm is proposed in this paper. SADE adjusts the mutation rate F and the crossover rate CR adaptively, taking account of the different distribution of population. In order to balance an individual's exploration and exploitation capability for different evolving phases, F and CR are equal to two different self-adjusted nonlinear functions. Attention is concentrated on varying F and CR dynamically with each generation evolution. SADE maintains the diversity of population and improves the global convergence ability. It also improves the efficiency and success rate and avoids the premature convergence. Simulation and comparisons based on test-sets of CSPs demonstrate the effectiveness, efficiency and robustness of the proposed algorithm. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码：2712 / 2718
页数：7
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