Cellular Differential Evolution Combined Opposition-Based Learning Initialization with Orthogonal Crossover

doi:10.13190/j.jbupt.2014.03.002

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2014, Vol. 37 ›› Issue (3): 7-12.doi: 10.13190/j.jbupt.2014.03.002

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Cellular Differential Evolution Combined Opposition-Based Learning Initialization with Orthogonal Crossover

DING Qing-feng^1,2, ZHENG Guo-xin¹, YANG Liu¹

1. Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Shanghai University, Shanghai 200072, China;
2. School of Electrical and Electronic Engineering, East China Jiaotong University, Nanchang 330013, China

Received:2013-07-25 Online:2014-06-28 Published:2014-06-08

Abstract

Abstract:

A cellular differential evolution (cDE)algorithm based on orthogonal crossover is presented. The opposition-based learning initialization is used to search better solution in the initial stage, the local search within cellular neighbourhood structure is presented to tune the selection pressure instead of the control parameters. And the parallel evolution mechanism of cellular automata is given to ensure the diversity of the evolution population. In addition, the orthogonal crossover is adopted to accelerate the convergence speed with multi-element repeated trials. The performance of the cDE algorithm is evaluated on a suite of classic benchmark functions and compared favorably with the canonical DE and several DE variants. Simulation shows the proposed algorithm has better convergence performance and higher calculation accuracy.

Key words: differential evolution, cellular automata, opposition-based learning, orthogonal crossover

CLC Number:

TN929.53

DING Qing-feng, ZHENG Guo-xin, YANG Liu. Cellular Differential Evolution Combined Opposition-Based Learning Initialization with Orthogonal Crossover[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2014, 37(3): 7-12.

References

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Cellular Differential Evolution Combined Opposition-Based Learning Initialization with Orthogonal Crossover

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