Paper Title:
An Improved Ant Colony Optimization Algorithm for Solving the TSP Problem
  Abstract

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, Y. J. Yang, Y. X. Sun, C. J. Zhang, T. L. Li, "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
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