Applied Intelligence

, Volume 32, Issue 1, pp 88–95

An enhanced ant colony optimization (EACO) applied to capacitated vehicle routing problem

  • Chou-Yuan Lee
  • Zne-Jung Lee
  • Shih-Wei Lin
  • Kuo-Ching Ying

DOI: 10.1007/s10489-008-0136-9

Cite this article as:
Lee, CY., Lee, ZJ., Lin, SW. et al. Appl Intell (2010) 32: 88. doi:10.1007/s10489-008-0136-9


In this paper, an enhanced ant colony optimization (EACO) is proposed for capacitated vehicle routing problem. The capacitated vehicle routing problem is to service customers with known demands by a homogeneous fleet of fixed capacity vehicles starting from a depot. It plays a major role in the field of logistics and belongs to NP-hard problems. Therefore, it is difficult to solve the capacitated vehicle routing problem directly when solutions increase exponentially with the number of serviced customers.

The framework of this paper is to develop an enhanced ant colony optimization for the capacitated vehicle routing problem. It takes the advantages of simulated annealing and ant colony optimization for solving the capacitated vehicle routing problem. In the proposed algorithm, simulated annealing provides a good initial solution for ant colony optimization. Furthermore, an information gain based ant colony optimization is used to ameliorate the search performance. Computational results show that the proposed algorithm is superior to original ant colony optimization and simulated annealing separately reported on fourteen small-scale instances and twenty large-scale instances.


Capacitated vehicle routing problem Hybrid algorithm Ant colony optimization Simulated annealing 

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Chou-Yuan Lee
    • 1
  • Zne-Jung Lee
    • 2
  • Shih-Wei Lin
    • 3
  • Kuo-Ching Ying
    • 4
  1. 1.Dept. of Information ManagementLan Yang Institute of TechnologyI LanTaiwan
  2. 2.Department of Information ManagementHuafan UniversityTaipei CountyTaiwan
  3. 3.Department of Information ManagementChang Gung UniversityTao-YuanTaiwan
  4. 4.Department of Industrial Engineering and Management InformationHuafan UniversityTaipei CountyTaiwan

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