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A large neighborhood search approach to the vehicle routing problem with delivery options

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  • Dumez, Dorian
  • Lehuédé, Fabien
  • Péton, Olivier

Abstract

To reduce delivery failures in last mile delivery, several types of delivery options have been proposed in the past twenty years. Still, customer satisfaction is a challenge because a single location is chosen independently of the time at which the customer’s order will be delivered. In addition, delivery at shared locations such as lockers and shops also experience failure due to capacity or opening-time issues at the moment of delivery. To address this issue and foster consolidation at shared delivery locations, we investigate the case where a customer can specify several delivery options together with preference levels and time windows. We define, in this article, the Vehicle Routing Problem with Delivery Options, which integrates several types of delivery locations. It consists of designing a set of routes for a fleet of vehicles that deliver to each customer at one of his/her options during the corresponding time window. These routes should respect capacities at shared locations such as lockers and minimum service level requirements, while minimizing the total routing costs. This problem is solved with a large neighborhood search in which a set partitioning problem is periodically used to reassemble routes. Specific ruin and recreate operators are proposed and combined with numerous operators from the literature. A thorough experimental study was carried out to determine a subset of efficient and complementary operators. The proposed method outperforms existing algorithms from the literature on particular cases of the problem under consideration, such as the vehicle routing problem with roaming delivery locations and the vehicle routing problem with home and roaming delivery locations. New instances are generated and used both to serve as a benchmark and to propose some managerial insight into the vehicle routing problem with alternative delivery options.

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  • Dumez, Dorian & Lehuédé, Fabien & Péton, Olivier, 2021. "A large neighborhood search approach to the vehicle routing problem with delivery options," Transportation Research Part B: Methodological, Elsevier, vol. 144(C), pages 103-132.
    • Handle: RePEc:eee:transb:v:144:y:2021:i:c:p:103-132
    DOI: 10.1016/j.trb.2020.11.012
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    1. L Moccia & J-F Cordeau & G Laporte, 2012. "An incremental tabu search heuristic for the generalized vehicle routing problem with time windows," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 63(2), pages 232-244, February.
    2. Ozbaygin, Gizem & Ekin Karasan, Oya & Savelsbergh, Martin & Yaman, Hande, 2017. "A branch-and-price algorithm for the vehicle routing problem with roaming delivery locations," Transportation Research Part B: Methodological, Elsevier, vol. 100(C), pages 115-137.
    3. Renaud Masson & Anna Trentini & Fabien Lehuédé & Nicolas Malhéné & Olivier Péton & Houda Tlahig, 2017. "Optimization of a city logistics transportation system with mixed passengers and goods," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 6(1), pages 81-109, March.
    4. 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.
    5. Hoogeboom, Maaike & Dullaert, Wout, 2019. "Vehicle routing with arrival time diversification," European Journal of Operational Research, Elsevier, vol. 275(1), pages 93-107.
    6. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part I: Route Construction and Local Search Algorithms," Transportation Science, INFORMS, vol. 39(1), pages 104-118, February.
    7. David Pisinger & Stefan Ropke, 2019. "Large Neighborhood Search," International Series in Operations Research & Management Science, in: Michel Gendreau & Jean-Yves Potvin (ed.), Handbook of Metaheuristics, edition 3, chapter 0, pages 99-127, Springer.
    8. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part II: Metaheuristics," Transportation Science, INFORMS, vol. 39(1), pages 119-139, February.
    9. Wouter Souffriau & Pieter Vansteenwegen & Greet Vanden Berghe & Dirk Van Oudheusden, 2013. "The Multiconstraint Team Orienteering Problem with Multiple Time Windows," Transportation Science, INFORMS, vol. 47(1), pages 53-63, February.
    10. Allahyari, Somayeh & Salari, Majid & Vigo, Daniele, 2015. "A hybrid metaheuristic algorithm for the multi-depot covering tour vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 242(3), pages 756-768.
    11. Timo Gschwind & Michael Drexl, 2019. "Adaptive Large Neighborhood Search with a Constant-Time Feasibility Test for the Dial-a-Ride Problem," Transportation Science, INFORMS, vol. 53(2), pages 480-491, March.
    12. Boysen, Nils & Schwerdfeger, Stefan & Weidinger, Felix, 2018. "Scheduling last-mile deliveries with truck-based autonomous robots," European Journal of Operational Research, Elsevier, vol. 271(3), pages 1085-1099.
    13. Florio, Alexandre M. & Feillet, Dominique & Hartl, Richard F., 2018. "The delivery problem: Optimizing hit rates in e-commerce deliveries," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 455-472.
    14. Zhou, Lin & Baldacci, Roberto & Vigo, Daniele & Wang, Xu, 2018. "A Multi-Depot Two-Echelon Vehicle Routing Problem with Delivery Options Arising in the Last Mile Distribution," European Journal of Operational Research, Elsevier, vol. 265(2), pages 765-778.
    15. Niels Agatz & Ann Campbell & Moritz Fleischmann & Martin Savelsbergh, 2011. "Time Slot Management in Attended Home Delivery," Transportation Science, INFORMS, vol. 45(3), pages 435-449, August.
    16. Marius M. Solomon & Jacques Desrosiers, 1988. "Survey Paper---Time Window Constrained Routing and Scheduling Problems," Transportation Science, INFORMS, vol. 22(1), pages 1-13, February.
    17. Vansteenwegen, Pieter & Souffriau, Wouter & Oudheusden, Dirk Van, 2011. "The orienteering problem: A survey," European Journal of Operational Research, Elsevier, vol. 209(1), pages 1-10, February.
    18. Jan Christiaens & Greet Vanden Berghe, 2020. "Slack Induction by String Removals for Vehicle Routing Problems," Transportation Science, INFORMS, vol. 54(2), pages 417-433, March.
    19. 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.
    20. Ghiani, Gianpaolo & Improta, Gennaro, 2000. "An efficient transformation of the generalized vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 122(1), pages 11-17, April.
    21. Christian Tilk & Katharina Olkis & Stefan Irnich, 2020. "The Last-mile Vehicle Routing Problem with Delivery Options," Working Papers 2017, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    22. Boysen, Nils & Schwerdfeger, Stefan & Weidinger, Felix, 2018. "Scheduling last-mile deliveries with truck-based autonomous robots," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 126189, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    23. Alberto Santini & Stefan Ropke & Lars Magnus Hvattum, 2018. "A comparison of acceptance criteria for the adaptive large neighbourhood search metaheuristic," Journal of Heuristics, Springer, vol. 24(5), pages 783-815, October.
    24. Chris Groër & Bruce Golden & Edward Wasil, 2011. "A Parallel Algorithm for the Vehicle Routing Problem," INFORMS Journal on Computing, INFORMS, vol. 23(2), pages 315-330, May.
    25. Timothy Curtois & Dario Landa-Silva & Yi Qu & Wasakorn Laesanklang, 2018. "Large neighbourhood search with adaptive guided ejection search for the pickup and delivery problem with time windows," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 7(2), pages 151-192, June.
    26. Michael Drexl, 2012. "Synchronization in Vehicle Routing---A Survey of VRPs with Multiple Synchronization Constraints," Transportation Science, INFORMS, vol. 46(3), pages 297-316, August.
    27. Demir, Emrah & Bektaş, Tolga & Laporte, Gilbert, 2012. "An adaptive large neighborhood search heuristic for the Pollution-Routing Problem," European Journal of Operational Research, Elsevier, vol. 223(2), pages 346-359.
    28. TURKEŠ, Renata & SÖRENSEN, Kenneth & HVATTUM, Lars Magnus & BARRENA, Eva & CHENTLI, Hayet & COELHO, Leandro & DAYARIAN, Iman & GRIMAULT, Axel & GULLHAVE, Anders & IRIS, Çagatay & KESKIN, Merve & KIEFE, 2019. "Meta-analysis of metaheuristics: Quantifying the effect of adaptiveness in adaptive large neighborhood search," Working Papers 2019002, University of Antwerp, Faculty of Business and Economics.
    29. Martin W. P. Savelsbergh, 1992. "The Vehicle Routing Problem with Time Windows: Minimizing Route Duration," INFORMS Journal on Computing, INFORMS, vol. 4(2), pages 146-154, May.
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    3. Nima Pourmohammadreza & Mohammad Reza Akbari Jokar, 2023. "A Novel Two-Phase Approach for Optimization of the Last-Mile Delivery Problem with Service Options," Sustainability, MDPI, vol. 15(10), pages 1-25, May.
    4. Mancini, Simona & Gansterer, Margaretha & Triki, Chefi, 2023. "Locker box location planning under uncertainty in demand and capacity availability," Omega, Elsevier, vol. 120(C).
    5. Frey, Christian M.M. & Jungwirth, Alexander & Frey, Markus & Kolisch, Rainer, 2023. "The vehicle routing problem with time windows and flexible delivery locations," European Journal of Operational Research, Elsevier, vol. 308(3), pages 1142-1159.
    6. Chane-Haï Timothée & Vercraene Samuel & Monteiro Thibaud, 2023. "The assignment-dial-a-ride-problem," Health Care Management Science, Springer, vol. 26(4), pages 770-784, December.
    7. Liu, Chuanju & Zhang, Junlong & Lin, Shaochong & Shen, Zuo-Jun Max, 2023. "Service network design with consistent multiple trips," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 171(C).
    8. Zhang, Yimeng & Li, Xinlei & van Hassel, Edwin & Negenborn, Rudy R. & Atasoy, Bilge, 2022. "Synchromodal transport planning considering heterogeneous and vague preferences of shippers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).

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