Paper Info
Title
Human Designed Vs. Genetically Programmed Differential Evolution Operators
Abstract
The hybridization and combination of different Evolutionary Algorithms to improve the quality of the solutions and to accelerate execution is a common research practice. In this paper, we utilize Genetic Programming to evolve novel Differential Evolution operators. The genetic evolution resulted in parameter free Differential Evolution operators. Our experimental results indicate that the performance of the genetically programmed operators is comparable and in some cases is considerably better than the already existing human designed ones.
Year
DOI
Venue
2006
10.1109/CEC.2006.1688536
IEEE Congress on Evolutionary Computation
Keywords
Field
DocType
genetic algorithms,genetic programming,genetically programmed differential evolution operators,human designed differential evolution operators
Genetic operator,Mathematical optimization,Evolutionary algorithm,Computer science,Meta-optimization,Evolutionary computation,Theoretical computer science,Evolution strategy,Genetic representation,Evolutionary programming,Quality control and genetic algorithms
Conference
ISBN
Citations 
PageRank 
0-7803-9487-9
8
0.54
References 
Authors
14
4
Name
Order
Citations
PageRank
N. G. Pavlidis12199.04
Plagianakos, V.P.217313.01
Dimitris K. Tasoulis3896.43
Michael N. Vrahatis417913.96