DocumentCode
2245639
Title
Differential Evolution with a local search operator
Author
Gu, Jirong ; Gu, Guojun
Author_Institution
Geogr. & Resources Sci. Coll., Sichuan Normal Univ., Chengdu, China
Volume
2
fYear
2010
fDate
6-7 March 2010
Firstpage
480
Lastpage
483
Abstract
Differential Evolution (DE) is a population-based stochastic search algorithm, which has shown good performance in many optimization problems. In this paper, we propose an improved DE algorithm, called LSDE, by using a local search operator to enhance the performance of classical DE. In order to verify the performance of LSDE, we test the proposed approach on seven well-known benchmark problems. The simulation results show that LSDE obtains good performance and outperforms the classical DE in all test cases.
Keywords
evolutionary computation; optimisation; search problems; stochastic processes; differential evolution; local search operator; optimization problems; stochastic search algorithm; Asia; Automatic control; Chromium; Electronic design automation and methodology; Evolutionary computation; Fuzzy logic; Genetic algorithms; Genetic mutations; Robotics and automation; Testing; differential evolution (DE); evolutionary computation; global optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Informatics in Control, Automation and Robotics (CAR), 2010 2nd International Asia Conference on
Conference_Location
Wuhan
ISSN
1948-3414
Print_ISBN
978-1-4244-5192-0
Electronic_ISBN
1948-3414
Type
conf
DOI
10.1109/CAR.2010.5456601
Filename
5456601
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