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The Time Window Assignment Vehicle Routing Problem with Time-Dependent Travel Times

Author

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  • Remy Spliet

    (Econometric Institute, Erasmus University, 3062 PA Rotterdam, Netherlands)

  • Said Dabia

    (Department of Information, Logistics and Innovation, Vrije University, 1081 HV Amsterdam, Netherlands)

  • Tom Van Woensel

    (Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology, 5600 MB Eindhoven, Netherlands)

Abstract

In this paper, we introduce the time window assignment vehicle routing problem (TWAVRP) with time-dependent travel times. It is the problem of assigning time windows to customers before their demand is known and creating vehicle routes adhering to these time windows after demand becomes known. The goal is to assign the time windows in such a way that the expected transportation costs are minimized. We develop a branch-price-and-cut algorithm to solve this problem to optimality. The pricing problem that has to be solved is a new variant of the shortest path problem, which includes a capacity constraint, time-dependent travel times, time window constraints on both the nodes and on the arcs, and linear node costs. For solving the pricing problem, we develop an exact labeling algorithm and a tabu search heuristic. Furthermore, we present new valid inequalities, which are specifically designed for the TWAVRP with time-dependent travel times. Finally, we present results of numerical experiments to illustrate the performance of the algorithm.

Suggested Citation

  • Remy Spliet & Said Dabia & Tom Van Woensel, 2018. "The Time Window Assignment Vehicle Routing Problem with Time-Dependent Travel Times," Transportation Science, INFORMS, vol. 52(2), pages 261-276, March.
    • Handle: RePEc:inm:ortrsc:v:52:y:2018:i:2:p:261-276
    DOI: 10.1287/trsc.2016.0705
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    References listed on IDEAS

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    Cited by:

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    2. Du, Jianhui & Zhang, Zhiqin & Wang, Xu & Lau, Hoong Chuin, 2023. "A hierarchical optimization approach for dynamic pickup and delivery problem with LIFO constraints," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    3. Subramanyam, Anirudh & Wang, Akang & Gounaris, Chrysanthos E., 2018. "A scenario decomposition algorithm for strategic time window assignment vehicle routing problems," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 296-317.
    4. Kevin Dalmeijer & Guy Desaulniers, 2021. "Addressing Orientation Symmetry in the Time Window Assignment Vehicle Routing Problem," INFORMS Journal on Computing, INFORMS, vol. 33(2), pages 495-510, May.
    5. Cuellar-Usaquén, Daniel & Ulmer, Marlin W. & Gomez, Camilo & Álvarez-Martínez, David, 2024. "Adaptive stochastic lookahead policies for dynamic multi-period purchasing and inventory routing," European Journal of Operational Research, Elsevier, vol. 318(3), pages 1028-1041.
    6. Côté, Jean-François & Mansini, Renata & Raffaele, Alice, 2024. "Multi-period time window assignment for attended home delivery," European Journal of Operational Research, Elsevier, vol. 316(1), pages 295-309.
    7. Neves-Moreira, Fábio & Pereira da Silva, Diogo & Guimarães, Luís & Amorim, Pedro & Almada-Lobo, Bernardo, 2018. "The time window assignment vehicle routing problem with product dependent deliveries," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 163-183.
    8. LIAN, Ying & LUCAS, Flavien & SÖRENSEN, Kenneth, 2022. "The on-demand bus routing problem with real-time traffic information," Working Papers 2022003, University of Antwerp, Faculty of Business and Economics.
    9. Lera-Romero, Gonzalo & Miranda-Bront, Juan José, 2021. "A branch and cut algorithm for the time-dependent profitable tour problem with resource constraints," European Journal of Operational Research, Elsevier, vol. 289(3), pages 879-896.
    10. Waßmuth, Katrin & Köhler, Charlotte & Agatz, Niels & Fleischmann, Moritz, 2023. "Demand management for attended home delivery—A literature review," European Journal of Operational Research, Elsevier, vol. 311(3), pages 801-815.
    11. Arpan Rijal & Marco Bijvank & Asvin Goel & René de Koster, 2021. "Workforce Scheduling with Order-Picking Assignments in Distribution Facilities," Transportation Science, INFORMS, vol. 55(3), pages 725-746, May.
    12. Lu, Jiawei & Nie, Qinghui & Mahmoudi, Monirehalsadat & Ou, Jishun & Li, Chongnan & Zhou, Xuesong Simon, 2022. "Rich arc routing problem in city logistics: Models and solution algorithms using a fluid queue-based time-dependent travel time representation," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 143-182.
    13. Stefan Faldum & Sarah Machate & Timo Gschwind & Stefan Irnich, 2024. "Partial dominance in branch-price-and-cut algorithms for vehicle routing and scheduling problems with a single-segment tradeoff," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 46(4), pages 1063-1097, December.
    14. Thomas R. Visser & Remy Spliet, 2020. "Efficient Move Evaluations for Time-Dependent Vehicle Routing Problems," Transportation Science, INFORMS, vol. 54(4), pages 1091-1112, July.
    15. Wassmuth, K. & Köhler, C. & Agatz, N.A.H. & Fleischmann, M., 2022. "Demand Management for Attended Home Delivery – A Literature Review," ERIM Report Series Research in Management ERS-2022-002-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    16. Vital, Filipe & Ioannou, Petros, 2022. "Optimizing Fuel Consumption and Pollutant Emissions in Truck Routing with Parking Availability Prediction and Working Hours Constraints," Institute of Transportation Studies, Working Paper Series qt8rw99523, Institute of Transportation Studies, UC Davis.
    17. Guo, Feng & Wei, Qu & Wang, Miao & Guo, Zhaoxia & Wallace, Stein W., 2023. "Deep attention models with dimension-reduction and gate mechanisms for solving practical time-dependent vehicle routing problems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
    18. Yang, Meng & Ni, Yaodong & Song, Qinyu, 2022. "Optimizing driver consistency in the vehicle routing problem under uncertain environment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).

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