An effective initialization strategy of pheromone for ant colony optimization

Author

Dai, Qiguo ; Ji, Junzhong ; Liu, Chunnian

Author_Institution

Beijing Municipal Key Lab. of Multimedia & Intell. Software Technol., Beijing Univ. of Technol., Beijing, China

fYear

2009

fDate

16-19 Oct. 2009

Firstpage

1

Lastpage

4

Abstract

Aiming at the poor performance of convergence of ant colony optimization (ACO), in this paper, a novel pheromone initialization strategy of ACO for the traveling salesman problem (TSP) is put forward. More precisely, the pheromone matrix of a specific ACO algorithm is initialized by the minimal spanning tree (MST) information. Simulation results demonstrate that the proposed strategy could improve the convergence performance of ACO both in term of quality of solution and speed of convergence.

Keywords

optimisation; travelling salesman problems; trees (mathematics); ACO; ant colony optimization; minimal spanning tree; pheromone initialization strategy; pheromone matrix; traveling salesman problem; Ant colony optimization; Cities and towns; Computer science; Educational institutions; Genetic mutations; Laboratories; NP-hard problem; Random variables; Software performance; Traveling salesman problems; ACO; MST; Pheromone; TSP;

fLanguage

English

Publisher

ieee

Conference_Titel

Bio-Inspired Computing, 2009. BIC-TA '09. Fourth International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-3866-2

Electronic_ISBN

978-1-4244-3867-9

Type

conf

DOI

10.1109/BICTA.2009.5338067

Filename

5338067