Advertisement

Multi-capacity, Multi-depot, Multi-product VRP with Heterogeneous Fleets and Demand Exceeding Depot Capacity

  • Gabriel Alemany
  • Angel A. Juan
  • Roberto Garcia
  • Alvaro Garcia
  • Miguel Ortega
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 730)

Abstract

This paper presents a four-step metaheuristic for addressing a rich and real-life vehicle routing problem. A set of customers request several products that must be delivered using a heterogeneous fleet of trucks with different compartments (one per product). These vehicles depart from a set of depots, which do not have enough capacity for meeting the aggregated customers’ demand of products. Therefore, some vehicles must visit an external facility at the beginning of their routes in order to obtain the necessary products to deliver. A real-world case has been solved, providing savings in reduced computing times.

Keywords

Logistics and transportation Combinatorial optimization Randomized algorithms Metaheuristics 

Notes

Acknowledgments

This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (TRA2013-48180-C3-P, TRA2015-71883-REDT), FEDER, and the Erasmus+ Program (2016-1-ES01-KA108-023465).

References

  1. 1.
    Caceres-Cruz, J., Arias, P., Guimarans, D., Riera, D., Juan, A.A.: Rich vehicle routing problem: survey. ACM Comput. Surv. (CSUR) 47(2), 32 (2015)Google Scholar
  2. 2.
    Clarke, G., Wright, J.W.: Scheduling of vehicles from a central depot to a number of delivery points. Oper. Res. 12(4), 568–581 (1964)CrossRefGoogle Scholar
  3. 3.
    Cornillier, F., Boctor, F.F., Laporte, G., Renaud, J.: A heuristic for the multi-period petrol station replenishment problem. Eur. J. Oper. Res. 191(2), 295–305 (2008)CrossRefMATHGoogle Scholar
  4. 4.
    Grasas, A., Juan, A.A., Faulin, J., De Armas, J., Ramalhinho, H.: Biased randomization of heuristics using skewed probability distributions: a survey and some applications. Comput. Ind. Eng. 110, 216–228 (2017)CrossRefGoogle Scholar
  5. 5.
    Henke, T., Speranza, M.G., Wäscher, G.: The multi-compartment vehicle routing problem with flexible compartment sizes. Eur. Oper. Res. 246(3), 730–743 (2015)MathSciNetCrossRefMATHGoogle Scholar
  6. 6.
    Juan, A.A., Faulin, J., Caceres-Cruz, J., Barrios, B.B., Martinez, E.: A successive approximations method for the heterogeneous vehicle routing problem: analyzing different fleet configurations. Eur. J. Ind. Eng. 8(6), 762–788 (2014)CrossRefGoogle Scholar
  7. 7.
    Juan, A.A., Faulin, J., Ferrer, A., Lourenço, H.R., Barrios, B.: MIRHA: multi-start biased randomization of heuristics with adaptive local search for solving non-smooth routing problems. Top 21(1), 109–132 (2013)MathSciNetCrossRefMATHGoogle Scholar
  8. 8.
    Juan, A.A., Faulin, J., Ruiz, R., Barrios, B., Gilibert, M., Vilajosana, X.: Using oriented random search to provide a set of alternative solutions to the capacitated vehicle routing problem. In: Operations Research and Cyber-Infrastructure, pp. 331–345. Springer, Boston (2009)Google Scholar
  9. 9.
    Juan, A.A., Pascual, I., Guimarans, D., Barrios, B.: Combining biased randomization with iterated local search for solving the multidepot vehicle routing problem. Int. Trans. Oper. Res. 22(4), 647–667 (2015)MathSciNetCrossRefMATHGoogle Scholar
  10. 10.
    Laporte, G.: What you should know about the vehicle routing problem. Naval Res. Logistics 54(8), 811–819 (2007)MathSciNetCrossRefMATHGoogle Scholar
  11. 11.
    Li, F., Golden, B., Wasil, E.: A record-to-record travel algorithm for solving the heterogeneous fleet vehicle routing problem. Comput. Oper. Res. 34(9), 2734–2742 (2007)CrossRefMATHGoogle Scholar
  12. 12.
    Pasquale, A., Maurizio, B., Antonio, S.: Solving a fuel delivery problem by heuristic and exact approaches. Eur. J. Oper. Res. 152(1), 170–179 (2004)MathSciNetCrossRefMATHGoogle Scholar
  13. 13.
    Prins, C.: A simple and effective evolutionary algorithm for the vehicle routing problem. Comput. Oper. Res. 31(12), 1985–2002 (2004)MathSciNetCrossRefMATHGoogle Scholar
  14. 14.
    Taillard, É.: A heuristic column generation method for the heterogeneous fleet VRP. RAIRO Oper. Res. 33(1), 1–14 (1999)MathSciNetCrossRefMATHGoogle Scholar
  15. 15.
    Tillman, F.A., Cain, T.M.: An upperbound algorithm for the single and multiple terminal delivery problem. Manag. Sci. 18(11), 664–682 (1972)CrossRefMATHGoogle Scholar
  16. 16.
    Wang, Q., Ji, Q., Chiu, C.H.: Optimal routing for heterogeneous fixed fleets of multicompartment vehicles. Math. Prob. Eng. 2013, 13 (2014)Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Gabriel Alemany
    • 1
  • Angel A. Juan
    • 1
  • Roberto Garcia
    • 2
  • Alvaro Garcia
    • 2
  • Miguel Ortega
    • 2
  1. 1.IN3 - Computer Science DepartmentOpen University of CataloniaBarcelonaSpain
  2. 2.Industrial Engineering DepartmentUniversidad Politecnica de MadridMadridSpain

Personalised recommendations