Title :
On Multi-Behavior Based Multi-Colony Ant Algorithm for TSP
Author :
Liu, Sheng ; You, Xiaoming
Author_Institution :
Sch. of Manage., Shanghai Univ. of Eng. Sci., Shanghai, China
Abstract :
To avoid premature convergence and stagnation problems in classical ant colony system, a novel multi-behavior based multi-colony ant algorithm (MBMCAA) is proposed. The ant colony is divided into several sub-colonies; the sub-colonies have their own population evolved independently and in parallel according to four different behavior options, and update their local pheromone and global pheromone level respectively according to immigrant operator. This parallel and cooperating optimization scheme by using different behavioral characteristics and inter-colonies migration strategies can help the algorithm skip from local optimum effectively. The experimental results for TSP show the validity of this algorithm.
Keywords :
optimisation; travelling salesman problems; cooperating optimization scheme; global pheromone; intercolonies migration strategy; local pheromone; multibehavior based multicolony ant algorithm; traveling salesman problem; Acceleration; Ant colony optimization; Approximation algorithms; Cities and towns; Convergence; Educational institutions; Engineering management; Information technology; Technology management; Traveling salesman problems; Ant Colony System(ACS); Traveling Salesman Problem (TSP); hybrid behavior; immigrant operator;
Conference_Titel :
Intelligent Information Technology Application, 2009. IITA 2009. Third International Symposium on
Conference_Location :
Nanchang
Print_ISBN :
978-0-7695-3859-4
DOI :
10.1109/IITA.2009.464
