Adaptive Differential Evolution: SHADE with Competing Crossover Strategies

被引:10
作者
Bujok, Petr [1 ]
Tvrdik, Josef [1 ]
机构
[1] Univ Ostrava, Dept Comp Sci, Ctr Excellence IT4Innovat, Inst Res & Applicat Fuzzy Modeling, CZ-70103 Ostrava, Czech Republic
来源
ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING, PT I | 2015年 / 9119卷
关键词
Global optimization; Differential evolution; Self-adaptation; Competing crossover; Experimental comparison; CEC 2013 test suite;
D O I
10.1007/978-3-319-19324-3_30
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Possible improvement of a successful adaptive SHADE variant of differential evolution is addressed. Exploitation of exponential crossover was applied in two newly proposed SHADE variants. The algorithms were compared experimentally on CEC 2013 test suite used as a benchmark. The results show that the variant using adaptive strategy of the competition of two types of crossover is significantly more efficient than other SHADE variants in 7 out of 28 problems and not worse in the others. Thus, this SHADE with competing crossovers can be considered superior to original SHADE algorithm.
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收藏
页码:329 / 339
页数:11
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