[1]刘三阳,张晓伟.混合差分变异策略[J].智能系统学报,2008,(06):487-491.
 LIU San-yang,ZHANG Xiao-wei.A hybrid strategy for differential variation[J].CAAI Transactions on Intelligent Systems,2008,(06):487-491.
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
期数:
2008年06期
页码:
487-491
栏目:
出版日期:
2008-12-25

文章信息/Info

Title:
A hybrid strategy for differential variation
文章编号:
1673-4785(2008)06-0487-05
作者:
刘三阳12张晓伟1
1.西安电子科技大学 数学科学系,陕西 西安 710071;2.西安电子科技大学 综合业务网国家重点实验室,陕西 西安 710071
Author(s):
LIU San-yang12ZHANG Xiao-wei1
1.Department of Mathematical Sciences, Xidian University, Xi’an 710071, China;2.State Key Lab.of ISN,Xidian University,Xi’an 710071,China
关键词:
全局优化粒子群优化差分进化
Keywords:
global optimization particle swarm optimization differential evolution
分类号:
TP18;O224
文献标志码:
A
摘要:
为了改善差分进化算法的求解性能,提出一种新的混合差分变异策略.该策略将种群中的每一个个体视作带电粒子,利用粒子所带的电荷量以及粒子之间的吸引排斥机制确定个体移动方向和位移大小.该策略会使个体在其他3个个体施加于它的力的方向上自适应地移动.数值实验表明基于该策略的差分进化算法求解精度高、评估次数少.
Abstract:
A new hybrid strategy for differential variation was developed in order to improve the performance of differential evolution. The strategy regards each individual in the population as a charged particle, and uses the charge level of the particle and the attraction-repulsion mechanism among particles to determine the probable direction and magnitude of motion. This strategy can compel individuals to move adaptively in the direction of the forces exerted on them by three other individuals. Numerical experiments showed that differential evolution based on this strategy has high accuracy and requires fewer evaluations.

参考文献/References:

[1]STORN R, PRICE K. Differential evolution—a simple and efficient heuristic for global optimization over continuous spaces[J]. Journal of Global Optimization, 1997, 11(4): 341-359.
[2]FEOKTSTOV V. Differential evolution: in search of solutions[M]. Berlin:Springer, 2006.
[3]QIN A, SUGANTHAN P. Self-adaptive differential evolution algorithm for numerical optimization[C]//Proceedings of the 2005 IEEE Congress on Evolutionary Computation. Edinburgh, UK, 2005(2):1785-1791.
[4]KIM H, CHONG J, PARK K, et al. Differential evolution strategy for constrained global optimization and application to practical engineering problems[J]. IEEE Transactions on Magnetics, 2007, 43(4):1565-1568.
[5]KENNEDY J, EBERHART R. Particle swarm optimization[C]//Proceedings of the IEEE International Joint Conference on Neural Networks. Perth, Australia.1995(4):1942-1948.
[6]BIRBIL S, FANG S. An electromagnetism like mechanism for global optimization[J]. Journal of Global Optimization,2003, 25(3):263-282.
[7]BIRBIL S, FANG S, SHEU R. On the convergence of a population-based global optimization[J]. Journal of Global Optimization,2004, 30(3):301-318.
[8]DEBELS D, REYCK B, LEUS R, et al. A hybrid scatter search/electromagnetism meta heuristic for project scheduling[J]. European Journal of Operational Research, 2006,169(2): 638-653.
[9]HAO Zhifeng, GUO Guanghan, HUANG Han. A particle swarm optimization algorithm with differential evolution[C]//Proceedings of the Sixth International Conference on Machine Learning and Cybernetics. Hong Kong, China, 2007(2):1031-1035.
[10]PRICE K. Differential evolution vs. the functions of the 2nd ICEO[C]//Proceeding of the 1997 IEEE International Conference on Evolutionary Computation. Indianapolis, USA,1997, 153-157.
[11]CLERC M, KENNEDY J. The particle swarm explosion, stability, and convergence in a multidimensional complex space[J]. IEEE Transactions on Evolutionary Computation, 2002, 6(1):58-73.

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备注/Memo

备注/Memo:
收稿日期:2008-07-04.
基金项目:国家自然科学基金资助项目(60574075, 60674108);综合业务网国家重点实验室基金资助项目(ISN 200806)
作者简介:
刘三阳,男,1959年生,博士,教授,博士生导师,国家教学名师.主要研究方向为应用数学、最优化和运筹学.现任西安电子科技大学理学院院长、工业与应用数学研究所所长.发表学术论文300余篇,出版专著10部.
张晓伟,男,1979年出生,博士研究生.主要研究方向为进化算法及最优化理论与方法.发表学术论文10余篇,其中被SCI、EI、ISTP检索7篇.
更新日期/Last Update: 2009-04-03