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Improved Ant Colony Algorithm for the Constrained Vehicle Routing

  • Guiqing Liu
  • Dengxu He
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 236)

Abstract

Using the basic ant colony algorithm to solve the constrained vehicle routing problem (CVRP) has some drawbacks such as slow convergence speed and easily getting into local optimum. To effectively solve the CVRP, this paper has proposed a new ant colony algorithm (ACA-CVRP) based on the dynamic update of local and global pheromone and improved transfer rule. In order to shorten the process, the authors introduced the candidate list and 2-opt searching strategy. The experiment result shows that ACA-CVRP achieves better performance in optimum solution compared with other five main meta-heuristic algorithms.

Keywords

Ant colony algorithm Pheromone update 2-opt Candidate list CVRP 

Notes

Acknowledgments

The first author is supported by the Youth Fund Project of Guangxi University for Nationalities (No. 2011MDQN038) and the open project of China-ASEAN Studies Center of Guangxi University for Nationalities (No. 2012012).

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.College of ASEANGuangxi University for NationalitiesNanningChina
  2. 2.College of ScienceGuangxi University for NationalitiesNanningChina

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