IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v287y2020i2p633-652.html
   My bibliography  Save this article

Route-based approximate dynamic programming for dynamic pricing in attended home delivery

Author

Listed:
  • Koch, Sebastian
  • Klein, Robert

Abstract

Attended home delivery describes the delivery of goods by e-grocers or e-tailers to customers within an agreed time window. Because customers expect narrow time windows, offering such services may lead to expensive fulfillment operations. This has led to research on how to influence customers’ bookings using time window pricing or slotting. In this paper, we reconsider the problem of demand management through dynamic pricing for attended home delivery services.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:287:y:2020:i:2:p:633-652
    DOI: 10.1016/j.ejor.2020.04.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221720303209
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2020.04.002?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. Carlos F. Daganzo, 1987. "Modeling Distribution Problems with Time Windows. Part II: Two Customer Types," Transportation Science, INFORMS, vol. 21(3), pages 180-187, August.
    2. Catherine Cleophas & Jan Ehmke, 2014. "When Are Deliveries Profitable?," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 6(3), pages 153-163, June.
    3. Stacy A. Voccia & Ann Melissa Campbell & Barrett W. Thomas, 2019. "The Same-Day Delivery Problem for Online Purchases," Service Science, INFORMS, vol. 53(1), pages 167-184, February.
    4. Ann Melissa Campbell & Martin W. P. Savelsbergh, 2005. "Decision Support for Consumer Direct Grocery Initiatives," Transportation Science, INFORMS, vol. 39(3), pages 313-327, August.
    5. 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.
    6. Carlos F. Daganzo, 1987. "Modeling Distribution Problems with Time Windows: Part I," Transportation Science, INFORMS, vol. 21(3), pages 171-179, August.
    7. 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.
    8. 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.
    9. Barrett W. Thomas, 2007. "Waiting Strategies for Anticipating Service Requests from Known Customer Locations," Transportation Science, INFORMS, vol. 41(3), pages 319-331, August.
    10. Ann Melissa Campbell & Martin Savelsbergh, 2006. "Incentive Schemes for Attended Home Delivery Services," Transportation Science, INFORMS, vol. 40(3), pages 327-341, August.
    11. Kyle D. Chen & Warren H. Hausman, 2000. "Technical Note: Mathematical Properties of the Optimal Product Line Selection Problem Using Choice-Based Conjoint Analysis," Management Science, INFORMS, vol. 46(2), pages 327-332, February.
    12. Lingxiu Dong & Panos Kouvelis & Zhongjun Tian, 2009. "Dynamic Pricing and Inventory Control of Substitute Products," Manufacturing & Service Operations Management, INFORMS, vol. 11(2), pages 317-339, December.
    13. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part II: Metaheuristics," Transportation Science, INFORMS, vol. 39(1), pages 119-139, February.
    14. Qian Liu & Garrett van Ryzin, 2008. "On the Choice-Based Linear Programming Model for Network Revenue Management," Manufacturing & Service Operations Management, INFORMS, vol. 10(2), pages 288-310, October.
    15. Martin Savelsbergh & Tom Van Woensel, 2016. "50th Anniversary Invited Article—City Logistics: Challenges and Opportunities," Transportation Science, INFORMS, vol. 50(2), pages 579-590, May.
    16. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, October.
    17. Klein, Robert & Koch, Sebastian & Steinhardt, Claudius & Strauss, Arne K., 2020. "A review of revenue management: Recent generalizations and advances in industry applications," European Journal of Operational Research, Elsevier, vol. 284(2), pages 397-412.
    18. James M. Davis & Huseyin Topaloglu & David P. Williamson, 2017. "Pricing Problems Under the Nested Logit Model with a Quality Consistency Constraint," INFORMS Journal on Computing, INFORMS, vol. 29(1), pages 54-76, February.
    19. 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.
    20. 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.
    21. Kraus, Ursula G. & Yano, Candace Arai, 2003. "Product line selection and pricing under a share-of-surplus choice model," European Journal of Operational Research, Elsevier, vol. 150(3), pages 653-671, November.
    22. Köhler, Charlotte & Ehmke, Jan Fabian & Campbell, Ann Melissa, 2020. "Flexible time window management for attended home deliveries," Omega, Elsevier, vol. 91(C).
    23. Robert Klein & Michael Neugebauer & Dimitri Ratkovitch & Claudius Steinhardt, 2019. "Differentiated Time Slot Pricing Under Routing Considerations in Attended Home Delivery," Service Science, INFORMS, vol. 53(1), pages 236-255, February.
    24. Dimitris Bertsimas & Ioana Popescu, 2003. "Revenue Management in a Dynamic Network Environment," Transportation Science, INFORMS, vol. 37(3), pages 257-277, August.
    25. Ann Melissa Campbell & Martin Savelsbergh, 2004. "Efficient Insertion Heuristics for Vehicle Routing and Scheduling Problems," Transportation Science, INFORMS, vol. 38(3), pages 369-378, August.
    26. Juan José Miranda Bront & Isabel Méndez-Díaz & Gustavo Vulcano, 2009. "A Column Generation Algorithm for Choice-Based Network Revenue Management," Operations Research, INFORMS, vol. 57(3), pages 769-784, June.
    27. Remy Spliet & Adriana F. Gabor, 2015. "The Time Window Assignment Vehicle Routing Problem," Transportation Science, INFORMS, vol. 49(4), pages 721-731, November.
    28. Agatz, Niels A.H. & Fleischmann, Moritz & van Nunen, Jo A.E.E., 2008. "E-fulfillment and multi-channel distribution - A review," European Journal of Operational Research, Elsevier, vol. 187(2), pages 339-356, June.
    29. Bruck, Bruno P. & Cordeau, Jean-François & Iori, Manuel, 2018. "A practical time slot management and routing problem for attended home services," Omega, Elsevier, vol. 81(C), pages 208-219.
    30. 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.
    31. Spliet, Remy & Desaulniers, Guy, 2015. "The discrete time window assignment vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 244(2), pages 379-391.
    32. Strauss, Arne K. & Klein, Robert & Steinhardt, Claudius, 2018. "A review of choice-based revenue management: Theory and methods," European Journal of Operational Research, Elsevier, vol. 271(2), pages 375-387.
    33. Marlin W. Ulmer & Dirk C. Mattfeld & Felix Köster, 2018. "Budgeting Time for Dynamic Vehicle Routing with Stochastic Customer Requests," Transportation Science, INFORMS, vol. 52(1), pages 20-37, January.
    34. Russell W. Bent & Pascal Van Hentenryck, 2004. "Scenario-Based Planning for Partially Dynamic Vehicle Routing with Stochastic Customers," Operations Research, INFORMS, vol. 52(6), pages 977-987, December.
    35. 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.
    36. Asdemir, Kursad & Jacob, Varghese S. & Krishnan, Ramayya, 2009. "Dynamic pricing of multiple home delivery options," European Journal of Operational Research, Elsevier, vol. 196(1), pages 246-257, July.
    37. Lu, Quan & Dessouky, Maged M., 2006. "A new insertion-based construction heuristic for solving the pickup and delivery problem with time windows," European Journal of Operational Research, Elsevier, vol. 175(2), pages 672-687, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Srinivas, Sharan & Ramachandiran, Surya & Rajendran, Suchithra, 2022. "Autonomous robot-driven deliveries: A review of recent developments and future directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).
    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. Gür Ali, Özden & Amorim, Pedro, 2024. "Personalized choice model for forecasting demand under pricing scenarios with observational data—The case of attended home delivery," International Journal of Forecasting, Elsevier, vol. 40(2), pages 706-720.
    5. Heydar, Mojtaba & Mardaneh, Elham & Loxton, Ryan, 2022. "Approximate dynamic programming for an energy-efficient parallel machine scheduling problem," European Journal of Operational Research, Elsevier, vol. 302(1), pages 363-380.
    6. Chen, Junlin & Xiong, Jinghong & Chen, Guobao & Liu, Xin & Yan, Peng & Jiang, Hai, 2024. "Optimal instant discounts of multiple ride options at a ride-hailing aggregator," European Journal of Operational Research, Elsevier, vol. 314(2), pages 718-734.
    7. Klein, Vienna & Steinhardt, Claudius, 2023. "Dynamic demand management and online tour planning for same-day delivery," European Journal of Operational Research, Elsevier, vol. 307(2), pages 860-886.
    8. 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.
    9. 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.

    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. 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.
    2. 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.
    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. Klein, Robert & Koch, Sebastian & Steinhardt, Claudius & Strauss, Arne K., 2020. "A review of revenue management: Recent generalizations and advances in industry applications," European Journal of Operational Research, Elsevier, vol. 284(2), pages 397-412.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Klein, Vienna & Steinhardt, Claudius, 2023. "Dynamic demand management and online tour planning for same-day delivery," European Journal of Operational Research, Elsevier, vol. 307(2), pages 860-886.
    11. Robert Klein & Michael Neugebauer & Dimitri Ratkovitch & Claudius Steinhardt, 2019. "Differentiated Time Slot Pricing Under Routing Considerations in Attended Home Delivery," Service Science, INFORMS, vol. 53(1), pages 236-255, February.
    12. Lang, Magdalena A.K. & Cleophas, Catherine & Ehmke, Jan Fabian, 2021. "Multi-criteria decision making in dynamic slotting for attended home deliveries," Omega, Elsevier, vol. 102(C).
    13. Magdalena A. K. Lang & Catherine Cleophas & Jan Fabian Ehmke, 2021. "Anticipative Dynamic Slotting for Attended Home Deliveries," SN Operations Research Forum, Springer, vol. 2(4), pages 1-39, December.
    14. Bruck, Bruno P. & Cordeau, Jean-François & Iori, Manuel, 2018. "A practical time slot management and routing problem for attended home services," Omega, Elsevier, vol. 81(C), pages 208-219.
    15. Haider, Zulqarnain & Hu, Yujie & Charkhgard, Hadi & Himmelgreen, David & Kwon, Changhyun, 2022. "Creating grocery delivery hubs for food deserts at local convenience stores via spatial and temporal consolidation," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    16. Visser, T.R. & Savelsbergh, M.W.P., 2019. "Strategic Time Slot Management: A Priori Routing for Online Grocery Retailing," Econometric Institute Research Papers EI2019-04, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    17. Stacy A. Voccia & Ann Melissa Campbell & Barrett W. Thomas, 2019. "The Same-Day Delivery Problem for Online Purchases," Service Science, INFORMS, vol. 53(1), pages 167-184, February.
    18. 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.
    19. 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.
    20. Agatz, N.A.H. & Fan, Y. & Stam, D.A., 2020. "Going green: the effect of green labels on delivery time slot choices," ERIM Report Series Research in Management ERS-2020-009-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:287:y:2020:i:2:p:633-652. 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.