Paper Info
Title
Differential evolution with adaptive repository of strategies and parameter control schemes
Abstract
A new Differential Evolution (ARDE) algorithm is introduced that automatically adapt a repository of DE strategies and parameters adaptation schemes of the mutation factor and the crossover rate to avoid the problems of stagnation and make DE responds to a wide range of function characteristics at different stages of the evolution. ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. Then a new adaptive procedure called adaptive repository (AR) has been developed to select the appropriate combinations of the JADE strategies and the parameter control schemes of the MDE_pBX to generate the next population based on their fitness values. Experimental results have been presented to confirm the reliability of the proposed ARDE over several existing adaptive DE variants. This comparison has been conducted in terms of the solution precision over twenty-one standard benchmark functions including CEC 2005 functions.
Year
DOI
Venue
2015
10.1109/CEC.2015.7256914
2015 IEEE Congress on Evolutionary Computation (CEC)
Keywords
Field
DocType
Evolutionary Algorithms,Adaptive Evolutionary Algorithm,Parameter Adaptive Scheme,Mutation Startegy
Convergence (routing),Population,Mathematical optimization,Computer science,Evolutionary computation,Differential evolution,Artificial intelligence,Crossover rate,Parameter control,Machine learning
Conference
ISSN
Citations 
PageRank 
1089-778X
0
0.34
References 
Authors
12
1
Name
Order
Citations
PageRank
Rawaa Dawoud Al-Dabbagh1242.13