DocumentCode :
581935
Title :
An efficient improved differential evolution algorithm
Author :
Dexuan, Zou ; Liqun, Gao
Author_Institution :
Sch. of Electr. Eng. & Autom., Jiangsu Normal Univ., Xuzhou, China
fYear :
2012
fDate :
25-27 July 2012
Firstpage :
2385
Lastpage :
2390
Abstract :
Differential evolution (DE) algorithm is a promising global optimization approach, but its control parameters are sensitive to some difficult problems, and they must be adjusted artificially for different problems some times, which is really a time consuming work. In this paper, we present a new version of DE with self-adaptive control parameters. We call the new version efficient improved differential evolution (EIDE). The EIDE modifies scale factor by using a uniform distribution, and modifies crossover rate by using a linear increasing strategy. Both strategies can avoid guessing the appropriate values for scale factor and crossover rate, and save the regulating time of the two parameters. Based on two groups of experiments, the EIDE has shown better convergence and stability than the other three DE algorithms in most cases.
Keywords :
adaptive control; evolutionary computation; stability; EIDE; efficient improved differential evolution algorithm; global optimization approach; self-adaptive control parameters; stability; Educational institutions; Evolution (biology); Evolutionary computation; Optimization; Sociology; Statistics; Vectors; Differential evolution; Efficient improved differential evolution; Global optimization; Self-adaptive control parameters;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2012 31st Chinese
Conference_Location :
Hefei
ISSN :
1934-1768
Print_ISBN :
978-1-4673-2581-3
Type :
conf
Filename :
6390324
Link To Document :
بازگشت