首页 | 本学科首页   官方微博 | 高级检索  
     检索      

差异演化算法的数值模拟研究
引用本文:袁俊刚,孙治国,曲广吉.差异演化算法的数值模拟研究[J].系统仿真学报,2007,19(20):4646-4648,4784.
作者姓名:袁俊刚  孙治国  曲广吉
作者单位:中国空间技术研究院总体部,北京,100094
摘    要:差异演化作为一种较新的演化算法,具有较强的寻优能力,但其优化性能受差异演化模式类型及演化控制参数取值的影响非常大。通过一组测试函数的数值模拟研究,给出了演化模式合理选取及演化参数(包括种群大小、交又概率及缩放因子)合适摹值的方法,解决了差异演化算法在应用时面临的一系列问题.此外,还基于演化能力较强的差异演化模式DE/rand/1/exp,提出了一种新的演化模式DE/rand2/1/exp,进一步提高了差异演化效率.

关 键 词:演化算法  差异演化  数值优化  算法改进
文章编号:1004-731X(2007)20-4646-03
收稿时间:2006-08-22
修稿时间:2006-08-222006-12-11

Simulation Study of Differential Evolution
YUAN Jun-gang,SUN Zhi-guo,QU Guang-ji.Simulation Study of Differential Evolution[J].Journal of System Simulation,2007,19(20):4646-4648,4784.
Authors:YUAN Jun-gang  SUN Zhi-guo  QU Guang-ji
Institution:China Academy of Space Technology, Beijing 100094, China
Abstract:Differential evolution (DE), as a new evolutionary algorithm, is characteristic of strong optimization capability. But its performance is strongly influenced by the variant of differential evolution and the value of each strategy parameter including population size, crossover probability and scale factor. Through a great deal of simulations with a set of test functions, the methods and skills of selecting the DE variant and assigning the strategy parameters values were obtained, resolving serials of problems when using DE. Based on the best variant DE/rand/1/exp, a new variant DE/rand2/1/exp was proposed, and its higher efficiency was showed with simulation.
Keywords:evolutionary algorithm  differential evolution  numerical optimization  algorithm improvement
本文献已被 CNKI 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号