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
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;
Conference_Titel :
Computing Colombian Conference (9CCC), 2014 9th
Conference_Location :
Pereira
DOI :
10.1109/ColumbianCC.2014.6955338
