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

Volume

3

fYear

2009

fDate

21-22 Nov. 2009

Firstpage

348

Lastpage

351

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Information Technology Application, 2009. IITA 2009. Third International Symposium on

Conference_Location

Nanchang

Print_ISBN

978-0-7695-3859-4

Type

conf

DOI

10.1109/IITA.2009.464

Filename

5370625