Paper Info
Title
Optimization and simulation research on Ant Colony Algorithm
Abstract
Aims at remedying the default of precocity and stagnation in the standard Ant Colony Algorithm(ACA),the rule of dynamic updating pheromones is presented, so that the area of feasible solutions are expanded, and the capability of global search is enhanced. Furthermore by introducing the dynamic updating strategy of parameters selection, the probability of solution mutation is increased, so dynamic adjusting the selected path is obtained,also with the improved solving. The simulation result on path planning which contains 32 nodes in a logistics distribution system shows that optimized ACA has excellent global optimization properties and faster the convergence speed, and it can avoid stasis phenomenon of ACA.
Year
DOI
Venue
2010
10.1109/ICNC.2010.5584898
ICNC
Keywords
Field
DocType
optimisation,global search capability,mutation probability,logistics distribution system,ant colony algorithm,search problems,pheromones,optimization,parameters selection,dynamic updating pheromones,dynamic updating strategy,probability,path planning,global optimization,algorithm design and analysis,solid modeling,logistic distribution,convergence
Ant colony optimization algorithms,Convergence (routing),Motion planning,Mathematical optimization,Algorithm design,Global optimization,Computer science,Distribution system,Artificial intelligence,Solid modeling,Mutation probability,Machine learning
Conference
Volume
ISBN
Citations 
8
978-1-4244-5958-2
0
PageRank 
References 
Authors
0.34
3
2
Name
Order
Citations
PageRank
Fengtao Lin100.68
Leping Liu252.33