DocumentCode
2909508
Title
Improved differential evolution for dynamic optimization problems
Author
Du Plessis, Mathys C. ; Engelbrecht, Andries P.
Author_Institution
Dept. of CS & IS, Nelson Mandela Metropolitan Univ., Port Elizabeth
fYear
2008
fDate
1-6 June 2008
Firstpage
229
Lastpage
234
Abstract
This article reports improvements on DynDE, a approach to using Differential Evolution to solve dynamic optimization problems. Three improvements are suggested, namely favored populations, migrating individuals and a combination of these approaches. The effects of varying the change frequency, peak widths and the number of dimensions of the dynamic environment are investigated. Experimental results are presented that indicate that the suggested approaches constitute considerable improvements on previous research.
Keywords
evolutionary computation; optimisation; differential evolution; dynamic environment; dynamic optimization; Chromium; Clustering algorithms; Evolutionary computation; Frequency; Genetic mutations; Heuristic algorithms; Multidimensional systems; Tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-1822-0
Electronic_ISBN
978-1-4244-1823-7
Type
conf
DOI
10.1109/CEC.2008.4630804
Filename
4630804
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