Paper Info
Title
Cellular Differential Evolution Algorithm
Abstract
This paper presents a cellular version of Differential Evolution (DE) algorithm. The notion behind the geographical distribution of DE population with local interaction is to study the influence of slow diffusion of information throughout the population. The study was carried out using the compact configuration of neighborhood from which all the auxiliary parents for DE recombination were selected. The empirical study was carried out using a standard benchmark suite consisting of 10 functions. The results show that the structured population with local interaction improves the convergence characteristics of DE and the performance improvement was also verified using scalability study. A brief comparison with cellular GA was also included.
Year
DOI
Venue
2010
10.1007/978-3-642-17432-2_30
AI 2010: ADVANCES IN ARTIFICIAL INTELLIGENCE
Keywords
Field
DocType
cellular differentiation,empirical study,differential evolution
Convergence (routing),Population,Mathematical optimization,Suite,Computer science,Differential evolution,Empirical research,Differential evolution algorithm,Scalability,Performance improvement
Conference
Volume
ISSN
Citations 
6464
0302-9743
8
PageRank 
References 
Authors
0.41
16
2
Name
Order
Citations
PageRank
Nasimul Noman132321.61
Hitoshi Iba21541138.51