An Improved Ant Colony Optimization Algorithm for Solving the TSP Problem

Abstract:

Article Preview

This paper presents a modified Ant Colony Algorithm(ACA) called route-update ant colony algorithm(RUACA). The research attention is focused on improving the computational efficiency in the TSP problem. A new impact factor is introduced and proved to be effective for reducing the convergence time in the RUACA performance. In order to assess the RUACA performance, a simply supported data set of cities, which was taken as the source data in previous research using traditional ACA and genetic algorithm(GA), is chosen as a benchmark case study. Comparing with the ACA and GA results, it is shown that the presented RUACA has successfully solved the TSP problem. The results of the proposed algorithm are found to be satisfactory.

Info:

Periodical:

Edited by:

Zhenyu Du and Bin Liu

Pages:

620-624

DOI:

10.4028/www.scientific.net/AMM.26-28.620

Citation:

Z. W. Du et al., "An Improved Ant Colony Optimization Algorithm for Solving the TSP Problem", Applied Mechanics and Materials, Vols. 26-28, pp. 620-624, 2010

Online since:

June 2010

Export:

Price:

$35.00

In order to see related information, you need to Login.

In order to see related information, you need to Login.