Paper Info
Title
Diversity enhanced adaptive evolutionary programming for solving single objective constrained problems
Abstract
In Evolutionary Algorithms, the occurrence of premature convergence is due to lack of diversity in the population during the search process. The effect may be more predominant if the optimization problem includes constraints. In this paper we propose an explicit memory based diversity enhancement Adaptive Evolutionary Programming (DivEnh-AEP) method to solve constraint optimization problems of CEC 2006.
Year
DOI
Venue
2009
10.1109/CEC.2009.4983201
IEEE Congress on Evolutionary Computation
Keywords
Field
DocType
convergence,evolutionary computation,optimisation,constraint optimization problem,diversity enhancement adaptive evolutionary programming,evolutionary algorithm,explicit memory,premature convergence,search process,single objective constrained problem
Convergence (routing),Population,Evolutionary algorithm,Computer science,Theoretical computer science,Artificial intelligence,Evolutionary programming,Optimization problem,Mathematical optimization,Premature convergence,Evolutionary computation,Probability density function,Machine learning
Conference
Citations 
PageRank 
References 
7
0.44
10
Authors
3
Name
Order
Citations
PageRank
Rammohan Mallipeddi1104549.50
P. N. Suganthan210876412.72
B. Y. Qu320311.67