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Heuristic Approaches for the Robust Vehicle Routing Problem

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Book cover Combinatorial Optimization (ISCO 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8596))

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Abstract

In this article, the Robust Vehicle Routing Problem (RVRP) with uncertain traveling costs is studied. It covers a number of important applications in urban transportation and large scale bio-terrorism emergency. The uncertain data are defined as a bounded set of discrete scenarios associated with each arc of the transportation network. The objective is to determine a set of vehicle routes minimizing the worst total cost over all scenarios. A mixed integer linear program is proposed to model the problem. Then, we adapt some classical VRP heuristics to the RVRP, such as Clarke and Wright, randomized Clarke and Wright, Sequential Best Insertion, Parallel Best Insertion and the Pilot versions of the Best Insertion heuristics. In addition, a local search is developed to improve the obtained solutions and be integrated in a Greedy Randomized Adaptive Search Procedure (GRASP). Computational results are presented for both the mathematical formulation and the proposed heuristics.

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References

  1. Toth, P., Vigo, D.: Exact solution of the vehicle routing problem. In: Fleet Management and Logistics, pp. 1–31 (1998)

    Google Scholar 

  2. Dantzig, G.B., Ramser, J.H.: The truck dispatching problem. Manage. Sci. 6, 80–91 (1959)

    Article  MATH  MathSciNet  Google Scholar 

  3. Achutan, N.R., Caccetta, L., Hill, S.P.: A new subtour elimination constraint for the vehicle routing problem. Eur. J. Oper. Res. 91, 573–586 (1996)

    Article  Google Scholar 

  4. Cordeau, J., Gendreau, M., Laporte, G., Potvin, J., Semet, F.: A guide to vehicle routing heuristics. J. Oper. Res. Soc. 53, 512–522 (2002)

    Article  MATH  Google Scholar 

  5. Brandão, J.: A deterministic tabu search algorithm for the fleet size and mix vehicle routing problem. Eur. J. Oper. Res. 19, 716–728 (2009)

    Article  Google Scholar 

  6. Moghaddam, B.F., Ruiz, R., Sadjadi, S.: Vehicle routing problem with uncertain demands: an advanced particle swarm algorithm. Comput. Ind. Eng. 62, 306–317 (2012)

    Article  Google Scholar 

  7. Golden, B.L., Yee, J.R.: A framework for probabilistic vehicle routing. AIIE Trans. 11, 109–112 (1979)

    Article  Google Scholar 

  8. Gendreau, M., Laporte, G., Seguin, R.: A tabu search heuristic for the vehicle routing problem with stochastic demands and customers. Oper. Res. 44, 469–477 (1996)

    Article  MATH  Google Scholar 

  9. Jula, H., Dessouky, M.M., Ioannou, P.: Truck route planning in non-stationary stochastic networks with time-windows at customer locations. IEEE Trans. Intell. Transp. Syst. 37, 51–63 (2006)

    Article  Google Scholar 

  10. Ai, J., Kachitvichyanukul, V.: A particle swarm optimization for the vehicle routing problem with simultaneous pickup and delivery. Comput. Oper. Res. 36, 1693–1702 (2009)

    Article  MATH  Google Scholar 

  11. Ben-Tal, A., Nemirovski, A.: Robust convex optimization. Math. Oper. Res. 23, 769–805 (1998)

    Article  MATH  MathSciNet  Google Scholar 

  12. El-Ghaoui, L., Oks, M., Oustry, F.: Worst-case value-at-risk and robust portfolio optimization: a conic programming approach. Oper. Res. 51, 543–556 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  13. Erera, A.L., Morales, J.C., Savelsbergh, M.: Robust optimization for empty repositioning problems. Oper. Res. 57, 468–483 (2009)

    Article  MATH  MathSciNet  Google Scholar 

  14. Tal, A.B., Golany, B., Nemirovski, A., Vial, J.: Supplier-retailer exible commitments contracts: a robust optimization approach. Manuf. Serv. Oper. Manage. 7, 248–273 (2005)

    Google Scholar 

  15. Atamturk, A., Zhang, M.: Two-stage robust network flow and design under demand uncertainty. Oper. Res. 55, 662–673 (2007)

    Article  MathSciNet  Google Scholar 

  16. Bertsimas, D., Simchi-Levi, D.: A new generation of vehicle routing research: robust algorithms, addressing uncertainty. Oper. Res. 44, 286–304 (1996)

    Article  MATH  Google Scholar 

  17. Ordóñez, F.: Robust vehicle routing. INFORMS TutORials Oper. Res. 7, 153–178 (2010)

    Google Scholar 

  18. Solano, E., Santos, A.C., Prins, C.: An overview on solving robust vehicle routing problem. In: 14ème congrès de la Société Française de Recherche Opérationnelle et d’Aide à la Décision (ROADEF) 2 p. (2013)

    Google Scholar 

  19. Sungur, I., Ordóñez, F., Dessouky, M.: A robust optimization approach for the capacitated vehicle routing problem with demand uncertainty. IIE Trans. 40, 509–523 (2008)

    Article  Google Scholar 

  20. Gounaris, C., Wiesemann, W., Floudas, C.A.: The robust capacitated vehicle routing problem under demand uncertainty. Oper. Res. 61, 677–693 (2013)

    Article  MATH  MathSciNet  Google Scholar 

  21. Erbao, C., Mingyong, L., Hongming, Y.: Open vehicle routing problem with demand uncertainty and its robust strategies. Expert Syst. Appl. 41, 3569–3575 (2014)

    Article  Google Scholar 

  22. Agra, A., Hvattum, L.M., Christiansen, M., Figuereido, R., Poss, M., Requejo, C.: The robust vehicle routing problem with time windows. Comput. Oper. Res. 40, 856–866 (2013)

    Article  MathSciNet  Google Scholar 

  23. Han, J., Lee, C., Park, S.: A robust scenario approach for the vehicle routing problem with uncertain travel times. Transp. Sci. 63, 1294–1306 (2013)

    Google Scholar 

  24. Toklu, N., Montemanni, R., Gambardella, L.M.: An ant colony system for the capacitated vehicle routing problem with uncertain travel costs, pp. 32–39 (2013)

    Google Scholar 

  25. Lee, C., Lee, K., Park, S.: Robust vehicle routing problem with deadlines and travel time/demand uncertainty. J. Oper. Res. Soc. 63, 1294–1306 (2012)

    Article  Google Scholar 

  26. Miller, C., Tucker, A., Zemlin, R.: Integer programming formulations and traveling salesman problems. J. ACM 7, 326–329 (1960)

    Article  MATH  MathSciNet  Google Scholar 

  27. Clarke, G., Wright, J.: Scheduling of vehicles from a central depot to a number of delivery points. Oper. Res. 12, 568–581 (1964)

    Article  Google Scholar 

  28. Solomon, M.M.: Algorithms for the vehicle routing and scheduling problem with time window constraints. Oper. Res. 35, 254–265 (1987)

    Article  MATH  MathSciNet  Google Scholar 

  29. Duis, C.W., Voss, S.: The pilot method: a strategy for heuristic repetition with application to the steiner problem in graphs. Networks 34, 181–191 (1999)

    Article  MathSciNet  Google Scholar 

  30. Feo, T., Resende, M.: A probabilistic heuristic for a computationally difficult set covering problem. Oper. Res. Lett. 8, 67–71 (1989)

    Article  MATH  MathSciNet  Google Scholar 

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Acknowledgements

This research is part of the project METHODI which is funded by the Champagne-Ardenne Region.

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Correspondence to Andréa Cynthia Santos .

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Solano-Charris, E.L., Prins, C., Santos, A.C. (2014). Heuristic Approaches for the Robust Vehicle Routing Problem. In: Fouilhoux, P., Gouveia, L., Mahjoub, A., Paschos, V. (eds) Combinatorial Optimization. ISCO 2014. Lecture Notes in Computer Science(), vol 8596. Springer, Cham. https://doi.org/10.1007/978-3-319-09174-7_33

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  • DOI: https://doi.org/10.1007/978-3-319-09174-7_33

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  • Publisher Name: Springer, Cham

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