DocumentCode
2832874
Title
An Improved Differential Evolution Alogorithm for Optimization
Author
Huibin, Jin ; Mingguang, Liu
Author_Institution
Res. Inst. of Civil Aviation Safety, Civil Aviation Univ. of China, Tianjin, China
fYear
2009
fDate
11-12 July 2009
Firstpage
659
Lastpage
662
Abstract
Differential Evolution (DE) is an efficient approach capable of handling non-differentiable, non-linear and multi-model objective functions. However, in convergence speed and global optimization, there is still much room for DE to be improved. In this paper, double best mutation operation and chaos Differential Evolution are proposed to improve DE algorithmpsilas optimized performance. The simulated cases show modified differential evolution algorithm has rapid convergence speed and strong steadiness.
Keywords
chaos; convergence; evolutionary computation; particle swarm optimisation; chaos differential evolution; convergence speed; double best mutation operation; particle swarm optimization; Automatic control; Automation; Chaos; Control systems; Convergence; Evolution (biology); Evolutionary computation; Genetic mutations; Nonlinear control systems; Stochastic processes; chaos differential evolution; differential evolution; double best mutation; particle swarm optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Control, Automation and Systems Engineering, 2009. CASE 2009. IITA International Conference on
Conference_Location
Zhangjiajie
Print_ISBN
978-0-7695-3728-3
Type
conf
DOI
10.1109/CASE.2009.116
Filename
5194541
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