Paper Title:
A Maturity-Based Adaptive Ant Colony Optimization Algorithm
  Abstract

In this paper, for the problems of low convergence rate and getting trapped in local optima easily, the average path similarity (APS) was proposed to present the optimization maturity by analyzing the relationship between parameters of local pheromone updating and global pheromone updating, as well as the optimizing capacity and convergence rate. Furthermore, the coefficients of pheromone updating adaptively were adjusted to improve the convergence rate and prevent the algorithm from getting stuck in local optima. The adaptive ACS has been applied to optimize several benchmark TSP instances. The solution quality and convergence rate of the algorithm were compared comprehensively with conventional ACS to verify the validity and the effectiveness.

  Info
Periodical
Edited by
Shaobo Zhong, Yimin Cheng and Xilong Qu
Pages
353-357
DOI
10.4028/www.scientific.net/AMM.50-51.353
Citation
H. N. Wang, S. Q. Sun, B. Liu, "A Maturity-Based Adaptive Ant Colony Optimization Algorithm", Applied Mechanics and Materials, Vols. 50-51, pp. 353-357, 2011
Online since
February 2011
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$32.00
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