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A Genetic Clustering Method for the Multi-Depot Vehicle Routing Problem

  • S. Salhi
  • S. R. Thangiah
  • F. Rahman

Abstract

A clustering method based on a genetic algorithm for solving the multi-depot routing problem is proposed. An efficient post optimiser enhanced by reduction tests is embedded into the search to further improve the solutions. Preliminary results, based on a set of problems given in the literature, are encouraging.

Keywords

Genetic Algorithm Travel Salesman Problem Genetic Cluster Vehicle Rout Problem Reduction Test 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1]
    I.M. Chao, B.L. Golden, and E. Wasil. A new heuristic for the multi-depot vehicle routing problem that improves upon best-known solutions. American Journal of Mathematical and Management Sciences, 13:371–401, 1993.MATHGoogle Scholar
  2. [2]
    F.H. Cullen. Set Partitioning Based Heuristics for Interactive Routing. PhD thesis, Georgia Institute of Technology, Georgia, 1984.Google Scholar
  3. [3]
    D.E. Goldberg. Genetic Algorthims in Search Optimization and Machine Learning. Addison Wesley, 1989.Google Scholar
  4. [4]
    B.L. Golden and A. Assad. Vehicle Routing: Methods and Studies. North Holland, Amsterdam, 1988.MATHGoogle Scholar
  5. [5]
    J.H. Holland. Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor, 1975.Google Scholar
  6. [6]
    G. Laporte. The vehicle routing problem: An overview of exact and approximate algorithms. European Journal of Operational Research, 59:345–358, 1992.MATHCrossRefGoogle Scholar
  7. [7]
    Parallel Genetic Algorithm Package. Argonne national laboratory. USA, 1996.Google Scholar
  8. [8]
    J. Perl and M.S. Daskin. A warehouse location routing problem. Transportation Research, 19B:381–396, 1985.Google Scholar
  9. [9]
    J. Renaud, G. Laporte, and F.F. Boctor. A tabu search heuristic for the multi-depot vehicle routing problem. Technical Report 94-44, Centre de Recherche sur les Transports, University of Montreal, Canada, 1994. Working Paper.Google Scholar
  10. [10]
    S. Salhi and G.K. Rand. Incorporating vehicle routing into the vehicle fleet composition problem. European Journal of Operational Research, 66:313–330, 1993.MATHCrossRefGoogle Scholar
  11. [11]
    S. Salhi and M. Sari. A multi-level composite heuristic for the multi-depot vehicle fleet mix problem. European Journal of Operational Research, 1997. (to appear).Google Scholar
  12. [12]
    S.R. Thangiah. Genetic Algorithms for Vehicle Routing Problems with Time Windows. CRC Press, Florida, 1996.Google Scholar
  13. [13]
    S.R. Thangiah, I.H. Osman, R. Vinayagamoorthy, and T. Sun. Algorithms for vehicle routing problems with time deadlines. American Journal of Mathematical and Management Sciences, 13:322–355, 1993.Google Scholar

Copyright information

© Springer-Verlag Wien 1998

Authors and Affiliations

  • S. Salhi
    • 1
  • S. R. Thangiah
    • 2
  • F. Rahman
    • 2
  1. 1.Management Mathematics Group, School of Mathematics and StatisticsUniversity of BirminghamUK
  2. 2.Computer Science DepartmentSlippery Rock UniversityUSA

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