DocumentCode
151874
Title
Optimization based on multi-type ants for the Traveling Salesman Problem
Author
Costa Salas, Y.J. ; Castano Perez, N.J. ; Betancur, J.F.
Author_Institution
Dept. of Econ., Univ. de Manizales, Manizales, Colombia
fYear
2014
fDate
3-5 Sept. 2014
Firstpage
144
Lastpage
149
Abstract
This paper proposes an algorithm based on multi-type ants (so-called Multi-type Ant Colony System, M-ACS) for solving the Traveling Salesman Problem (TSP). Multiple ant types cooperate (through pheromone exchange) and compete (by mean of repulsion mechanism) among them in order to increase the efficacy in the search process. The obtained experimental results has been compared against benchmark results from OR literature. In particular for large scale TSP, the algorithmic proposal M-ACS shows competitive results regarding to the efficacy.
Keywords
ant colony optimisation; travelling salesman problems; M-ACS; OR literature; large scale TSP; multitype ant based optimization; multitype ant colony system; pheromone exchange; repulsion mechanism; search process; traveling salesman problem; Electronic mail; Genetic algorithms; Heuristic algorithms; Libraries; Particle swarm optimization; Roads; Traveling salesman problems; ant algorithms; bioinspired computation; multi-type ants; optimization; traveling salesman;
fLanguage
English
Publisher
ieee
Conference_Titel
Computing Colombian Conference (9CCC), 2014 9th
Conference_Location
Pereira
Type
conf
DOI
10.1109/ColumbianCC.2014.6955338
Filename
6955338
Link To Document