A 2-Opt based differential evolution for global optimization

Authors:
Cheng-Wen Chiang;Wei-Ping Lee;Jia-Sheng Heh
Affiliations:
Department of Electronic Engineering, Chung Yuan Christian University, Chung Li City, Taoyuan County 320, Taiwan, ROC;Department of Management Information Systems, Chung Yuan Christian University, Chung Li City, Taoyuan County 320, Taiwan, ROC;Department of Electronic Engineering, Chung Yuan Christian University, Chung Li City, Taoyuan County 320, Taiwan, ROC
Venue:
Applied Soft Computing
Year:
2010

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Abstract

Differential evolution (DE) is a simple and effective global optimization algorithm. It has been successfully applied to solve a wide range of real-world optimization problems. However, DE has shown some weaknesses, especially the long computational times because of its stochastic nature. This drawback sometimes limits its application to optimization problems. Therefore we propose the 2-Opt based DE (2-Opt DE) which is inspired by 2-Opt algorithms to accelerate DE. The novel mutation schemes of 2-Opt DE, DE/2-Opt/1 and DE/2-Opt/2 are substituted for mutation schemes of the original DE namely DE/rand/1 and DE/rand/2. We also provide a comparison of 2-Opt DE to DE. A comprehensive set of 19 benchmark functions is employed for experimental verification. The experimental results confirm that 2-Opt DE outperforms the original DE in terms of solution accuracy and convergence speed.