Combining semantically-effective and geometric crossover operators for genetic programming

被引：0
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作者：
机构：
[1] Pawlak, Tomasz P.
来源：
Pawlak, Tomasz P. (tpawlak@cs.put.poznan.pl) | 1600年 / Springer Verlag卷 / 8672期
关键词：
Genetic programming - Geometry - Genetic algorithms;
D O I：
10.1007/978-3-319-10762-2_45
中图分类号：
学科分类号：
摘要：
We propose a way to combine two distinct general patterns for designing semantic crossover operators for genetic programming: geometric semantic approach and semantically-effective approach. In the experimental part we show the synergistic effects of combining these two approaches, which we explain by a major fraction of crossover acts performed by geometric semantic crossover operators being semantically ineffective. The results of the combined approach show significant improvement of performance and high resistance to a premature convergence. © Springer International Publishing Switzerland 2014.
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