[1]梁静,周钦亚,瞿博阳,等.基于混合策略的差分进化算法[J].郑州大学学报(工学版),2013,34(05):59-62.[doi:10.3969/j.issn.1671-6833.2013.05.013]
　LIANG Jing,ZHOU Qin-ya,QU Bo-yang,et al.Differential Evolution Algorithm Based on Hybrid Strategy[J].Journal of Zhengzhou University (Engineering Science),2013,34(05):59-62.[doi:10.3969/j.issn.1671-6833.2013.05.013]
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基于混合策略的差分进化算法()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
34
期数:
2013年05期
页码:
59-62
栏目:
出版日期:
2013-09-10

文章信息/Info

Title:
Differential Evolution Algorithm Based on Hybrid Strategy
作者:
梁静; 周钦亚; 瞿博阳; 等.
郑州大学电气工程学院,河南郑州,450001, 中原工学院电子信息学院,河南郑州,450007
Author(s):
LIANG Jing1; ZHOU Qin-ya1; QU Bo-yang12; SONG Hui1
1.School of Electrical Engineering, Zhengzhou University , Zhengzhou 450001 , China;2. School of Electric and Information En-gineering，Zhongyuan University of ’Technology，Zhengzhou 450007，China
关键词:
差分进化算法;  多种群;  混合策略
Keywords:
differential evolution algorithm; multi-population ;  hybrid strategy
分类号:
TP301.6
DOI:
10.3969/j.issn.1671-6833.2013.05.013
摘要:
针对传统差分进化算法在求解问题中种群易收敛、易早熟的问题,提出了一种基于混合策略的差分进化算法.该算法根据粒子适应度、适应度标准差和粒子间距离标准差,将种群分为3个不同大小、不同功能的子种群,每个子种群采用不同策略和控制参数来实现自己被指定的功能.算法在搜索过程中既增强了种群的全局搜索能力,又增加了收敛精度.通过对4个标准函数的测试,仿真结果表明该算法比其他算法具有更好的寻优能力.
Abstract:
In this paper,a differential evolution algorithm based on hybrid strategy was proposed to solve thetraditional differential evolution algorithm which is easy to convergence and premature in solving high-dimen-sional problems. This algorithm divided the population into three sub-populations of different sizes and differ-ent functions according to the fitness, standard deviation of fitness and distance of particles.Each sub-popula-tion used different strategies and parameters to achieve their specific functions. It not only enhances the globalsearch ability of the population,but also increases the precision of convergence during the search process.Having tasted four classic benchmarks problems,the experiment results show that the proposed algorithm is aneffective method for different optimization problems.

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更新日期/Last Update: 1900-01-01