Improved ant colony optimization algorithm solve logistics distribution center allocation

  • Authors:

  • Xiao Jian-Mei;Wang Xi-Huai;Fu Yu

  • Affiliations:

  • College of Logistics Engineering, Shanghai Maritime University, Shanghai, China;College of Logistics Engineering, Shanghai Maritime University, Shanghai, China;College of Logistics Engineering, Shanghai Maritime University, Shanghai, China

  • Venue:
  • CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
  • Year:
  • 2009

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Abstract

The rational layout and location of logistics center has a great impact on the function and overall profit of it. In this paper, according to the characteristics and requirements in the selection of the location, an improved ant colony algorithm is applied to the location selection. A dynamic local updating rule is presented in later cycle. Reduce the pheromone of the routes that are not selected by ants, increase the difference between the better routes and the worse routes, enhance the convergent speed of the algorithm and decrease the run time. The calculation results show that the improved ant colony algorithm has good performance, and it is available to solve distribution center location selection.