An Experimental Study of the Ant Colony System for the Period Vehicle Routing Problem

  • Ana Cristina Matos
  • Rui Carvalho Oliveira
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3172)


In this paper, a new Ant System approach to the Period Vehicle Routing Problem (PVRP) is presented. In PVRP, visit days have to be assigned to customers in order to find efficient routes over the period. We suggest a new technique for defining the initial solution and a novel strategy to update the pheromone trails that is especially suited for solving large scale problems. An illustrative example for a waste collection system involving 202 localities in the municipality of Viseu, Portugal, demonstrates the effectiveness of the model.


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  1. 1.
    Beltrami, E.J., Bodin, L.D.: Networks and vehicle routing for municipal waste collection. Networks 4, 65–94 (1974)zbMATHCrossRefGoogle Scholar
  2. 2.
    Bullnheimer, B., Hartl, R.F., Strauss, C.: An improved ant system algorithm for the vehicle routing problem. Annals of Operations Research 89, 319–328 (1999)zbMATHCrossRefMathSciNetGoogle Scholar
  3. 3.
    Bullnheimer, B., Hartl, R.F., Strauss, C.: A new rank based version of the ant system: a computational study. Working Paper No.1,SFB Adaptative Information Systems and Modelling in Economics and Management Science, Vienna (1997)Google Scholar
  4. 4.
    Chao, I.M., Golden, B.L., Wasil, E.A.: An improved heuristic for the period vehicle routing problem. Networks 26, 25–44 (1995)zbMATHCrossRefMathSciNetGoogle Scholar
  5. 5.
    Clarke, G., Wright, J.W.: Scheduling of vehicles from a central depot to a number of delivery points. Operations Research 12, 568–581 (1964)CrossRefGoogle Scholar
  6. 6.
    Colorni, A., Dorigo, M., Maniezzo, V.: Distributed optimization by ant colonies. In: Varela, F., Bourgine, P. (eds.) Proc.Europ. Conf. Artificial Life, pp. 134–142. Elsevier, Amsterdam (1992)Google Scholar
  7. 7.
    Cordeau, J.F., Gendreau, M., Laporte, G.: A tabu search heuristic for periodic and multi-depot vehicle routing problems. Networks 30, 105–119 (1997)zbMATHCrossRefGoogle Scholar
  8. 8.
    Dorigo, M., Gambardella, L.M.: Ant colony system: a cooperative learning approach to the traveling salesman problem. IEEE Transactions on Evolutionary Computation 1(1), 53–66 (1997)CrossRefGoogle Scholar
  9. 9.
    Dorigo, M., Maniezzo, V., Colorni, A.: The ant system: optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man and Cybernetics - Part B 26(1), 29–41 (1996)CrossRefGoogle Scholar
  10. 10.
    Doerner, K.F., Gronalt, M., Hartl, R.F., Reimann, M.: Optimizing pickup and delivery operations in a hub network with ant systems. POM Working Paper 02/2000, University of Vienna, Vienna, Austria (2000)Google Scholar
  11. 11.
    Osman, H.: Metastrategy simulated annealing and tabu search algorithms for vehicle routing problem. Annals of Opertations Research 41, 412–451 (1993)Google Scholar
  12. 12.
    Reimann, M., Stummer, M., Doerner, K.: A savings based ant system for the vehicle routing problem. In: Proc. of the Genetic and Evolutionary Computation Conference, pp. 1317–1362 (2002)Google Scholar
  13. 13.
    Russell, R.A., Gribbin, D.: A multiphase approach to the period routing problem. Networks 21, 747–765 (1991)zbMATHCrossRefGoogle Scholar
  14. 14.
    Vianna, D., Ochi, L., Drummond, L.: A parallel hybrid evolutionary metaheuristic for the period vehicle routing problem. In: Proc. IPDPS (1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Ana Cristina Matos
    • 1
  • Rui Carvalho Oliveira
    • 2
  1. 1.Escola Superior de TecnologiaInstituto Politécnico de ViseuViseuPortugal
  2. 2.CESUR/DECInstituto Superior TécnicoLisboaPortugal

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