Paper Info
Title
A New Population Migration Algorithm Based on the Chaos Theory
Abstract
In order to improve the solution accuracy and the convergence of Population Migration Algorithm (PMA) and avoiding its prematurity, in this paper, we combined chaos theory with PMA. By introducing logistic mapping of chaos theory into PMA, we use the ergodicity, randomicity and regularity of chaos theory to attain an improved algorithm. The experimental results show that: by introducing the ergodicity, randomicity and regularity of chaos theory into PMA, the solution accuracy and the convergence property of PMA can effectively improve and effectively avoid prematurity phenomenon. The improved algorithm performs very well.
Year
DOI
Venue
2011
10.1109/IPTC.2011.44
IPTC
Keywords
Field
DocType
optimisation,swarm intelligence,ergodicity,randomicity,convergence property,chaos,combined chaos theory,logistic mapping,chaos theory,population migration algorithm,solution accuracy,algorithm theory,improved algorithm,new population migration algorithm,prematurity phenomenon,convergence,logistic map,optimization,accuracy,logistics,algorithm design and analysis
Convergence (routing),Population,New population,Ergodicity,Algorithm design,Computer science,Swarm intelligence,Algorithm,Logistic mapping,Chaos theory
Conference
ISBN
Citations 
PageRank 
978-1-4577-1130-5
0
0.34
References 
Authors
2
2
Name
Order
Citations
PageRank
Yuwu Lu119612.50
Xueying Liu222.05