Real Parameter Single Objective Optimization using Self-Adaptive Differential Evolution Algorithm with more Strategies

被引：0
|
作者：
Brest, Janez [1 ]
Boskovic, Borko [1 ]
Zamuda, Ales [1 ]
Fister, Iztok [1 ]
Mezura-Montes, Efren [2 ]
机构：
[1] Univ Maribor, Fac Elect Engn & Comp Sci, Inst Comp Sci, Smetanova Ul 17, SLO-2000 Maribor, Slovenia
[2] Univ Veracruzana, Dept Inteligencia Artificial, Xalapa 91000, Veracruz, Mexico
来源：
2013 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC) | 2013年
关键词：
single objective optimization; differential evolution; self-adaptation;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
A new differential evolution algorithm for single objective optimization is presented in this paper. The proposed algorithm uses a self-adaptation mechanism for parameter control, divides its population into more subpopulations, applies more DE strategies, promotes population diversity, and eliminates the individuals that are not changed during some generations. The experimental results obtained by our algorithm on the benchmark consisting of 25 test functions with dimensions D = 10, D = 30, and D = 50 as provided for the CEC 2013 competition and special session on Real Parameter Single Objective Optimization are presented.
引用
收藏
页码：377 / 383
页数：7
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