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
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;
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
DOI :
10.1109/CEC.2008.4630804
