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工程设计学报
Chinese Journal of Engineering Design  2012, Vol. 19 Issue (5): 372-378    DOI:
    
Research on differential evolution algorithm based on Gauss mutation and its application
 LU  Qing-Bo1,2, ZHANG  Xue-Liang1, WEN  Shu-Hua1, LAN  Guo-Sheng1, LIU  Li-Qin1
1.College of Mechanical Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China;
2. Zhengzhou Technical College, Zhengzhou 450121, China
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Abstract  In order to balance the convergence rate and the global searching ability and overcome the premature convergence of the differential evolution algorithm, a modified differential evolution algorithm based on Gauss mutation (GMDE) was proposed. The paper provided a detailed analysis of population diversity descent and individual stagnant evolution and then incorporated the Gauss mutation into differential evolution. The optimization performance of GMDE was evaluated and the results of numerical simulation and two engineering optimization design examples show that the proposed algorithm can overcome the premature convergence efficiently and can obtain a better balance of convergence rate and the global searching ability.

Key words： differential evolution algorithm      Gauss mutation      crossover rate     
Published: 28 October 2012
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LU Qing-Bo
ZHANG Xue-Liang
WEN Shu-Hua
LAN Guo-Sheng
LIU Li-Qin
Cite this article:

LU Qing-Bo, ZHANG Xue-Liang, WEN Shu-Hua, LAN Guo-Sheng, LIU Li-Qin. Research on differential evolution algorithm based on Gauss mutation and its application. Chinese Journal of Engineering Design, 2012, 19(5): 372-378.

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https://www.zjujournals.com/gcsjxb/     OR     https://www.zjujournals.com/gcsjxb/Y2012/V19/I5/372


高斯变异差分进化算法及其应用研究

为平衡算法收敛速度和全局搜索能力,克服差分进化算法易“早熟”的缺陷,在分析引起种群多样性下降及个体进化停滞原因的基础上,通过引入高斯变异操作,提出了基于高斯变异改进的差分进化算法(modified differential evolution base on Gauss mutation, GMDE). 数值仿真及2个工程优化问题的求解结果表明本文算法能有效避免“早熟”收敛,且在算法收敛速度和全局搜索能力上取得了较好的平衡.

关键词： 差分进化算法,  高斯变异,  交叉率 
[1] HU Jing-jing, LI Guo-yong, ZHANG Yan-long. The friction modeling and feed-forward compensation based on differential evolution algorithm[J]. Chinese Journal of Engineering Design, 2016, 23(5): 431-436.