An Effective Improvement of JADE for Real-parameter Optimization

被引：0
|
作者：
Zhang, Chunjiang [1 ]
Gao, Liang [1 ]
机构：
[1] Huazhong Univ Sci & Technol, State Key Lab Digital Mfg Equipment & Technol, Wuhan 430074, Peoples R China
来源：
2013 SIXTH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTATIONAL INTELLIGENCE (ICACI) | 2013年
关键词：
Differential evolution; Improved JADE; Real-parameter optimization; DIFFERENTIAL EVOLUTION;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Although the metaheuristics cannot guarantee to find the optimum for global optimization, they are efficient indeed, especially for the problems very difficultly be optimized by traditional optimization methods. Differential evolution algorithm is one of the most competitive metaheuristics and the adaptive DE with optional external archive (JADE) is an excellent DE-variant. Based on the analysis of shortcomings of JADE, an effective improvement of JADE is put forward in this paper. Two parameters in JADE can be reinitialized and two new mutation strategies are added in the improved JADE. 28 benchmark problems for competition on real-parameter single objective optimization in 2013 IEEE Congress on Evolutionary Computation (CEC 2013) are used to test the performance of the proposed algorithm. The results compared with DE/rand/1 and original JADE shows the improvement is effective.
引用
收藏
页码：58 / 63
页数：6
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