Differential Evolution Algorithm based on Self-adaptive Adjustment Mechanism

被引：0
|
作者：
Wang, Xu [1 ]
Zhao, Shuguang [1 ]
Jin, Yanling [1 ]
Zhang, Lijuan [1 ]
机构：
[1] Donghua Univ, Coll Informat Sci & Technol, Shanghai 201620, Peoples R China
来源：
2013 25TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC) | 2013年
关键词：
Differential evolution (DE); Self-adaptation; Real-value optimization; Population regulation;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Differential evolution algorithm is a strong effective method for optimization problems. Parameter setting is one crucial point to improve the DE's performance. Hence, a DE based on self-adaptive adjustment mechanism (SAMDE) is proposed to tune the size of offspring population NP besides mutation scale factor F and crossover constant Cr automatically. Moreover, the proposed algorithm applies a DE strategies pool to adjust mutation strategy during different evolution stage. Testing the algorithms on multimodal or complex continuous benchmark functions, we find that the proposed SAMDE performs better than classic DE algorithms. Performance comparisons with JADE are also significant.
引用
收藏
页码：577 / 581
页数：5
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