Solving Vehicle Routing Problem Using Ant Colony and Genetic Algorithm

  • Wen Peng
  • Chang-Yu Zhou
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 15)

Abstract

Vehicle routing problem becomes more remarkable with the development of modern logistics. Ant colony and genetic algorithm are combined for solving vehicle routing problem. GA can overcome the drawback of premature and weak exploitation capabilities of ant colony and converge to the global optimal quickly. The performance of the proposed method as compared to those of the genetic-based approaches is very promising.

Keywords

ant colony vehicle routing problem genetic algorithm 

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References

  1. 1.
    Dorigo, M.: Optimization, learning and natural algorithms. Ph.D. Thesis, Italy (1992)Google Scholar
  2. 2.
    Huang, K., Liao, C.: Ant colony optimization combined with taboo search for the job shop scheduling problem. Computers and Operations Research 35, 1030–1046 (2008)MATHCrossRefGoogle Scholar
  3. 3.
    Jian, S., Jian, S., Lin, B.M.T., Hsiao, T.: Ant colony optimization for the cell assignment problem in PCS networks. Computer and Operations Research 33, 1731–1740 (2006)Google Scholar
  4. 4.
    McMullen, P.R.: An ant colony optimization approach to addressing a JIT sequencing problem with multiple objectives. Artificial Intelligence 15(3), 309–317 (2001)CrossRefGoogle Scholar
  5. 5.
    Bell, J.E., McMullen, P.R.: Ant Colony Optimization Techniques for the Vehicle Routing Problem. Advanced Engineering Informatics 1(8), 41–48 (2004)CrossRefGoogle Scholar
  6. 6.
    Tavakkoli-Moghaddam, R., Safaei, N., Gholipour, Y.: A hybrid simulated annealing for capacitated vehicle routing problems with the independent route length. Applied Mathematics and Computation 176, 445–454 (2006)MATHCrossRefMathSciNetGoogle Scholar
  7. 7.
    Prins, C.: A simple and effective evolutionary algorithm for the vehicle routing problem. Computers & Operations Research 31, 1985–2002 (2004)MATHCrossRefMathSciNetGoogle Scholar
  8. 8.
    Brandao, J., Mercer, A.: A Tabu Search Algorithm for the Multi-Trip Vehicle Routing and Scheduling Problem. European Journal of Operational Research 100, 180–191 (1997)MATHCrossRefGoogle Scholar
  9. 9.
    Doerner, K.F., Hartl, R.F., Kiechle, G., Lucka, M., Reimann, M.: Parallel Ant Systems for the Capacitated Vehicle Routing Problem. In: Gottlieb, J., Raidl, G.R. (eds.) EvoCOP 2004. LNCS, vol. 3004, pp. 72–83. Springer, Heidelberg (2004)Google Scholar
  10. 10.
    Liu, L., Zhu, J.: The Research of Optimizing Physical Distribution Routing Based on Genetic Algorithm. Computer Engineering and Application 27, 227–229 (2005)MathSciNetGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Wen Peng
    • 1
  • Chang-Yu Zhou
    • 1
  1. 1.School of Computer Science and TechnologyNorth China Electric Power UniversityBeijing 

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