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Proceedings Paper

Differential evolution based on hybrid crossover operators
Author(s): Lei Yang; Long Zhou; Min Yu
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Paper Abstract

Differential evolution (DE) is a newly proposed intelligent optimization algorithm, which has shown good search abilities in many optimization problems. However, DE as well as other population-based stochastic algorithms can be easily trapped into local optima when solving complex multimodal problems. In order to enhance the performance of DE, this paper presents a novel DE variant (HCDE) based on hybrid crossover operators. Simulation studies on ten wellknown benchmark functions show that the proposed approach HCDE achieves better results when compared with other two DE variants.

Paper Details

Date Published: 1 October 2011
PDF: 6 pages
Proc. SPIE 8285, International Conference on Graphic and Image Processing (ICGIP 2011), 828578 (1 October 2011); doi: 10.1117/12.913516
Show Author Affiliations
Lei Yang, Wuhan Polytechnic Univ. (China)
Long Zhou, Wuhan Univ. of Technology (China)
Min Yu, Wuhan Univ. of Technology (China)


Published in SPIE Proceedings Vol. 8285:
International Conference on Graphic and Image Processing (ICGIP 2011)

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