IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v310y2023i1p168-184.html
   My bibliography  Save this article

Dynamic multi-period vehicle routing with touting

Author

Listed:
  • Keskin, Merve
  • Branke, Juergen
  • Deineko, Vladimir
  • Strauss, Arne K.

Abstract

This paper introduces a dynamic multi-period vehicle routing problem with touting as demand management technique, where customers that have not yet placed an order can be actively encouraged to order a service sooner. Touting the right customers, such as those located nearby customers who already placed orders, allows for more efficient routes over time. However, it also increases the frequency of visits at such touted customers as they are serviced before they would normally require, which leads to smaller demand volumes per visit. To tackle this trade-off, we propose several strategies to decide which customers to tout and when, using the characteristics of the customers as well as the current plan at the time of touting. Specifically, using the demand and the location information, we approach the ones which are close to the current tour, relatively far from the depot and not likely to easily be covered in the near future. This information is then used as a part of different touting strategies, which are further embedded in a rolling-time horizon vehicle routing algorithm to address the multi-period nature of the problem. These different strategies are empirically compared in a simulation based on a real-world waste collection problem. We demonstrate that touting indeed allows to significantly reduce the travel distance in a dynamic vehicle routing problem.

Suggested Citation

  • Keskin, Merve & Branke, Juergen & Deineko, Vladimir & Strauss, Arne K., 2023. "Dynamic multi-period vehicle routing with touting," European Journal of Operational Research, Elsevier, vol. 310(1), pages 168-184.
  • Handle: RePEc:eee:ejores:v:310:y:2023:i:1:p:168-184
    DOI: 10.1016/j.ejor.2023.02.037
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221723001856
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2023.02.037?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Pillac, Victor & Gendreau, Michel & Guéret, Christelle & Medaglia, Andrés L., 2013. "A review of dynamic vehicle routing problems," European Journal of Operational Research, Elsevier, vol. 225(1), pages 1-11.
    2. 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.
    3. Ozbaygin, Gizem & Savelsbergh, Martin, 2019. "An iterative re-optimization framework for the dynamic vehicle routing problem with roaming delivery locations," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 207-235.
    4. Ulrike Ritzinger & Jakob Puchinger & Richard F. Hartl, 2016. "A survey on dynamic and stochastic vehicle routing problems," International Journal of Production Research, Taylor & Francis Journals, vol. 54(1), pages 215-231, January.
    5. Xinan Yang & Arne K. Strauss & Christine S. M. Currie & Richard Eglese, 2016. "Choice-Based Demand Management and Vehicle Routing in E-Fulfillment," Transportation Science, INFORMS, vol. 50(2), pages 473-488, May.
    6. Ulmer, Marlin W. & Soeffker, Ninja & Mattfeld, Dirk C., 2018. "Value function approximation for dynamic multi-period vehicle routing," European Journal of Operational Research, Elsevier, vol. 269(3), pages 883-899.
    7. Jan Brinkmann & Marlin W. Ulmer & Dirk C. Mattfeld, 2020. "The multi-vehicle stochastic-dynamic inventory routing problem for bike sharing systems," Business Research, Springer;German Academic Association for Business Research, vol. 13(1), pages 69-92, April.
    8. Christian Billing & Florian Jaehn & Thomas Wensing, 2018. "A multiperiod auto-carrier transportation problem with probabilistic future demands," Journal of Business Economics, Springer, vol. 88(7), pages 1009-1028, September.
    9. Niels Agatz & Yingjie Fan & Daan Stam, 2021. "The Impact of Green Labels on Time Slot Choice and Operational Sustainability," Production and Operations Management, Production and Operations Management Society, vol. 30(7), pages 2285-2303, July.
    10. 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.
    11. Yildiz, Baris & Savelsbergh, Martin, 2020. "Pricing for delivery time flexibility," Transportation Research Part B: Methodological, Elsevier, vol. 133(C), pages 230-256.
    12. Warren B. Powell & Michael T. Towns & Arun Marar, 2000. "On the Value of Optimal Myopic Solutions for Dynamic Routing and Scheduling Problems in the Presence of User Noncompliance," Transportation Science, INFORMS, vol. 34(1), pages 67-85, February.
    13. De Bruecker, Philippe & Beliën, Jeroen & De Boeck, Liesje & De Jaeger, Simon & Demeulemeester, Erik, 2018. "A model enhancement approach for optimizing the integrated shift scheduling and vehicle routing problem in waste collection," European Journal of Operational Research, Elsevier, vol. 266(1), pages 278-290.
    14. Soeffker, Ninja & Ulmer, Marlin W. & Mattfeld, Dirk C., 2022. "Stochastic dynamic vehicle routing in the light of prescriptive analytics: A review," European Journal of Operational Research, Elsevier, vol. 298(3), pages 801-820.
    15. Anirudh Subramanyam & Frank Mufalli & José M. Lí?nez-Aguirre & Jose M. Pinto & Chrysanthos E. Gounaris, 2021. "Robust Multiperiod Vehicle Routing Under Customer Order Uncertainty," Operations Research, INFORMS, vol. 69(1), pages 30-60, January.
    16. Dayarian, Iman & Crainic, Teodor Gabriel & Gendreau, Michel & Rei, Walter, 2016. "An adaptive large-neighborhood search heuristic for a multi-period vehicle routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 95-123.
    17. 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.
    18. Ketzenberg, Michael E. & Metters, Richard D., 2020. "Adapting operations to new information technology: A failed “internet of things” application," Omega, Elsevier, vol. 92(C).
    19. Markov, Iliya & Bierlaire, Michel & Cordeau, Jean-François & Maknoon, Yousef & Varone, Sacha, 2018. "A unified framework for rich routing problems with stochastic demands," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 213-240.
    20. Yang, Xinan & Strauss, Arne K., 2017. "An approximate dynamic programming approach to attended home delivery management," European Journal of Operational Research, Elsevier, vol. 263(3), pages 935-945.
    21. Patrick Jaillet & Jonathan F. Bard & Liu Huang & Moshe Dror, 2002. "Delivery Cost Approximations for Inventory Routing Problems in a Rolling Horizon Framework," Transportation Science, INFORMS, vol. 36(3), pages 292-300, August.
    22. Cordeau, Jean-François & Dell’Amico, Mauro & Falavigna, Simone & Iori, Manuel, 2015. "A rolling horizon algorithm for auto-carrier transportation," Transportation Research Part B: Methodological, Elsevier, vol. 76(C), pages 68-80.
    23. Theodore Athanasopoulos & Ioannis Minis, 2013. "Efficient techniques for the multi-period vehicle routing problem with time windows within a branch and price framework," Annals of Operations Research, Springer, vol. 206(1), pages 1-22, July.
    24. Gábor Nagy & Niaz A. Wassan & M. Grazia Speranza & Claudia Archetti, 2015. "The Vehicle Routing Problem with Divisible Deliveries and Pickups," Transportation Science, INFORMS, vol. 49(2), pages 271-294, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Jian & Woensel, Tom Van, 2023. "Dynamic vehicle routing with random requests: A literature review," International Journal of Production Economics, Elsevier, vol. 256(C).
    2. Fleckenstein, David & Klein, Robert & Steinhardt, Claudius, 2023. "Recent advances in integrating demand management and vehicle routing: A methodological review," European Journal of Operational Research, Elsevier, vol. 306(2), pages 499-518.
    3. Avraham, Edison & Raviv, Tal, 2021. "The steady-state mobile personnel booking problem," Transportation Research Part B: Methodological, Elsevier, vol. 154(C), pages 266-288.
    4. Nikola Mardešić & Tomislav Erdelić & Tonči Carić & Marko Đurasević, 2023. "Review of Stochastic Dynamic Vehicle Routing in the Evolving Urban Logistics Environment," Mathematics, MDPI, vol. 12(1), pages 1-44, December.
    5. 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.
    6. Abdollahi, Mohammad & Yang, Xinan & Nasri, Moncef Ilies & Fairbank, Michael, 2023. "Demand management in time-slotted last-mile delivery via dynamic routing with forecast orders," European Journal of Operational Research, Elsevier, vol. 309(2), pages 704-718.
    7. Koch, Sebastian & Klein, Robert, 2020. "Route-based approximate dynamic programming for dynamic pricing in attended home delivery," European Journal of Operational Research, Elsevier, vol. 287(2), pages 633-652.
    8. Aziez, Imadeddine & Côté, Jean-François & Coelho, Leandro C., 2022. "Fleet sizing and routing of healthcare automated guided vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    9. María I. Restrepo & Frédéric Semet & Thomas Pocreau, 2019. "Integrated Shift Scheduling and Load Assignment Optimization for Attended Home Delivery," Transportation Science, INFORMS, vol. 53(4), pages 1150-1174, July.
    10. Zhang, Jian & Luo, Kelin & Florio, Alexandre M. & Van Woensel, Tom, 2023. "Solving large-scale dynamic vehicle routing problems with stochastic requests," European Journal of Operational Research, Elsevier, vol. 306(2), pages 596-614.
    11. Yuki Oyama & Daisuke Fukuda & Naoto Imura & Katsuhiro Nishinari, 2022. "E-commerce users' preferences for delivery options," Papers 2301.00666, arXiv.org, revised Aug 2023.
    12. Robert Klein & Jochen Mackert & Michael Neugebauer & Claudius Steinhardt, 2018. "A model-based approximation of opportunity cost for dynamic pricing in attended home delivery," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(4), pages 969-996, October.
    13. He, Dongdong & Guan, Wei, 2023. "Promoting service quality with incentive contracts in rural bus integrated passenger-freight service," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(C).
    14. Baals, Julian & Emde, Simon & Turkensteen, Marcel, 2023. "Minimizing earliness-tardiness costs in supplier networks—A just-in-time truck routing problem," European Journal of Operational Research, Elsevier, vol. 306(2), pages 707-741.
    15. Amir Saeed Nikkhah Qamsari & Seyyed-Mahdi Hosseini-Motlagh & Seyed Farid Ghannadpour, 2022. "A column generation approach for an inventory routing problem with fuzzy time windows," Operational Research, Springer, vol. 22(2), pages 1157-1207, April.
    16. Ehmke, Jan Fabian & Campbell, Ann Melissa, 2014. "Customer acceptance mechanisms for home deliveries in metropolitan areas," European Journal of Operational Research, Elsevier, vol. 233(1), pages 193-207.
    17. Stefan Vonolfen & Michael Affenzeller, 2016. "Distribution of waiting time for dynamic pickup and delivery problems," Annals of Operations Research, Springer, vol. 236(2), pages 359-382, January.
    18. Strauss, Arne & Gülpınar, Nalan & Zheng, Yijun, 2021. "Dynamic pricing of flexible time slots for attended home delivery," European Journal of Operational Research, Elsevier, vol. 294(3), pages 1022-1041.
    19. Liu, Yiming & Roberto, Baldacci & Zhou, Jianwen & Yu, Yang & Zhang, Yu & Sun, Wei, 2023. "Efficient feasibility checks and an adaptive large neighborhood search algorithm for the time-dependent green vehicle routing problem with time windows," European Journal of Operational Research, Elsevier, vol. 310(1), pages 133-155.
    20. van der Hagen, L. & Agatz, N.A.H. & Spliet, R. & Visser, T.R. & Kok, A.L., 2022. "Machine Learning-Based Feasibility Checks for Dynamic Time Slot Management," ERIM Report Series Research in Management ERS-2022-001-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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:310:y:2023:i:1:p:168-184. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.