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An Adaptive Large Neighborhood Search Heuristic for the Pickup and Delivery Problem with Time Windows

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  • Stefan Ropke

    (DIKU, University of Copenhagen, Universitetsparken 1, DK-2100 Copenhagen, Denmark)

  • David Pisinger

    (DIKU, University of Copenhagen, Universitetsparken 1, DK-2100 Copenhagen, Denmark)

Abstract

The pickup and delivery problem with time windows is the problem of serving a number of transportation requests using a limited amount of vehicles. Each request involves moving a number of goods from a pickup location to a delivery location. Our task is to construct routes that visit all locations such that corresponding pickups and deliveries are placed on the same route, and such that a pickup is performed before the corresponding delivery. The routes must also satisfy time window and capacity constraints.This paper presents a heuristic for the problem based on an extension of the large neighborhood search heuristic previously suggested for solving the vehicle routing problem with time windows. The proposed heuristic is composed of a number of competing subheuristics that are used with a frequency corresponding to their historic performance. This general framework is denoted adaptive large neighborhood search .The heuristic is tested on more than 350 benchmark instances with up to 500 requests. It is able to improve the best known solutions from the literature for more than 50% of the problems.The computational experiments indicate that it is advantageous to use several competing subheuristics instead of just one. We believe that the proposed heuristic is very robust and is able to adapt to various instance characteristics.

Suggested Citation

  • Stefan Ropke & David Pisinger, 2006. "An Adaptive Large Neighborhood Search Heuristic for the Pickup and Delivery Problem with Time Windows," Transportation Science, INFORMS, vol. 40(4), pages 455-472, November.
    • Handle: RePEc:inm:ortrsc:v:40:y:2006:i:4:p:455-472
    DOI: 10.1287/trsc.1050.0135
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    References listed on IDEAS

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    1. Dumas, Yvan & Desrosiers, Jacques & Soumis, Francois, 1991. "The pickup and delivery problem with time windows," European Journal of Operational Research, Elsevier, vol. 54(1), pages 7-22, September.
    2. Ropke, Stefan & Pisinger, David, 2006. "A unified heuristic for a large class of Vehicle Routing Problems with Backhauls," European Journal of Operational Research, Elsevier, vol. 171(3), pages 750-775, June.
    3. Potvin, Jean-Yves & Rousseau, Jean-Marc, 1993. "A parallel route building algorithm for the vehicle routing and scheduling problem with time windows," European Journal of Operational Research, Elsevier, vol. 66(3), pages 331-340, May.
    4. Marius M. Solomon, 1987. "Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints," Operations Research, INFORMS, vol. 35(2), pages 254-265, April.
    5. Russell Bent & Pascal Van Hentenryck, 2004. "A Two-Stage Hybrid Local Search for the Vehicle Routing Problem with Time Windows," Transportation Science, INFORMS, vol. 38(4), pages 515-530, November.
    6. Nanry, William P. & Wesley Barnes, J., 2000. "Solving the pickup and delivery problem with time windows using reactive tabu search," Transportation Research Part B: Methodological, Elsevier, vol. 34(2), pages 107-121, February.
    7. J-F Cordeau & G Laporte & A Mercier, 2001. "A unified tabu search heuristic for vehicle routing problems with time windows," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(8), pages 928-936, August.
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