Power mean based crossover rate adaptive differential evolution

Authors:
Jie Li;Wujie Zhu;Mengjun Zhou;Hua Wang
Affiliations:
School of Computer & Information, Hefei University of Technology, Hefei, China;School of Computer & Information, Hefei University of Technology, Hefei, China;School of Computer & Information, Hefei University of Technology, Hefei, China;School of Computer & Information, Hefei University of Technology, Hefei, China
Venue:
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part II
Year:
2011

Citing 3
Cited 1

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Repairing the crossover rate in adaptive differential evolution

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Abstract

Crossover rate (CR) is a key parameter affecting the operation of differential evolution (DE). According to the different status appear in CR adaptive process, the present paper employs power mean averaging operators to improve the value of CR in appropriate chance and propose a Power Mean based Crossover Rate Adaptive Differential Evolution (PMCRADE). The performance of PMCRADE is evaluated on a set of benchmark problems and is compared with conventional and state-of-the-art DE variants. The results show that PMCRADE is better than, or at least comparable to, the compared DE variants in terms of convergence speed and reliability.