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Deep Q-learning for same-day delivery with vehicles and drones

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  • Chen, Xinwei
  • Ulmer, Marlin W.
  • Thomas, Barrett W.

Abstract

In this paper, we consider same-day delivery with vehicles and drones. Customers make delivery requests over the course of the day, and the dispatcher dynamically dispatches vehicles and drones to deliver the goods to customers before their delivery deadline. Vehicles can deliver multiple packages in one route but travel relatively slowly due to the urban traffic. Drones travel faster, but they have limited capacity and require charging or battery swaps. To exploit the different strengths of the fleets, we propose a deep Q-learning approach. Our method learns the value of assigning a new customer to either drones or vehicles as well as the option to not offer service at all. In a systematic computational analysis, we show the superiority of our policy compared to benchmark policies and the effectiveness of our deep Q-learning approach. We also show that the combination of state and action features is very valuable and that our policy can maintain effectiveness when demand data and the fleet size change moderately.

Suggested Citation

  • Chen, Xinwei & Ulmer, Marlin W. & Thomas, Barrett W., 2022. "Deep Q-learning for same-day delivery with vehicles and drones," European Journal of Operational Research, Elsevier, vol. 298(3), pages 939-952.
    • Handle: RePEc:eee:ejores:v:298:y:2022:i:3:p:939-952
    DOI: 10.1016/j.ejor.2021.06.021
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    References listed on IDEAS

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    1. Mathias A. Klapp & Alan L. Erera & Alejandro Toriello, 2018. "The One-Dimensional Dynamic Dispatch Waves Problem," Transportation Science, INFORMS, vol. 52(2), pages 402-415, March.
    2. Alejandro Toriello & William B. Haskell & Michael Poremba, 2014. "A Dynamic Traveling Salesman Problem with Stochastic Arc Costs," Operations Research, INFORMS, vol. 62(5), pages 1107-1125, October.
    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. Iman Dayarian & Martin Savelsbergh & John-Paul Clarke, 2020. "Same-Day Delivery with Drone Resupply," Transportation Science, INFORMS, vol. 54(1), pages 229-249, January.
    5. Klapp, Mathias A. & Erera, Alan L. & Toriello, Alejandro, 2018. "The Dynamic Dispatch Waves Problem for same-day delivery," European Journal of Operational Research, Elsevier, vol. 271(2), pages 519-534.
    6. Pérez Rivera, Arturo E. & Mes, Martijn R.K., 2017. "Anticipatory freight selection in intermodal long-haul round-trips," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 105(C), pages 176-194.
    7. Powell, Warren B., 2019. "A unified framework for stochastic optimization," European Journal of Operational Research, Elsevier, vol. 275(3), pages 795-821.
    8. Nabila Azi & Michel Gendreau & Jean-Yves Potvin, 2012. "A dynamic vehicle routing problem with multiple delivery routes," Annals of Operations Research, Springer, vol. 199(1), pages 103-112, October.
    9. 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.
    10. 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.
    11. Ulmer, Marlin W. & Thomas, Barrett W., 2020. "Meso-parametric value function approximation for dynamic customer acceptances in delivery routing," European Journal of Operational Research, Elsevier, vol. 285(1), pages 183-195.
    12. Klapp, Mathias A. & Erera, Alan L. & Toriello, Alejandro, 2020. "Request acceptance in same-day delivery," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    13. Iman Dayarian & Martin Savelsbergh, 2020. "Crowdshipping and Same‐day Delivery: Employing In‐store Customers to Deliver Online Orders," Production and Operations Management, Production and Operations Management Society, vol. 29(9), pages 2153-2174, September.
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    2. Zhang, Jian & Woensel, Tom Van, 2023. "Dynamic vehicle routing with random requests: A literature review," International Journal of Production Economics, Elsevier, vol. 256(C).
    3. Chen, Xinwei & Wang, Tong & Thomas, Barrett W. & Ulmer, Marlin W., 2023. "Same-day delivery with fair customer service," European Journal of Operational Research, Elsevier, vol. 308(2), pages 738-751.
    4. Liu, Zeyu & Li, Xueping & Khojandi, Anahita, 2022. "The flying sidekick traveling salesman problem with stochastic travel time: A reinforcement learning approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
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    6. Pina-Pardo, Juan C. & Silva, Daniel F. & Smith, Alice E. & Gatica, Ricardo A., 2024. "Fleet resupply by drones for last-mile delivery," European Journal of Operational Research, Elsevier, vol. 316(1), pages 168-182.
    7. Banerjee, Dipayan & Erera, Alan L. & Stroh, Alexander M. & Toriello, Alejandro, 2023. "Who has access to e-commerce and when? Time-varying service regions in same-day delivery," Transportation Research Part B: Methodological, Elsevier, vol. 170(C), pages 148-168.
    8. 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.
    9. Peter Dieter & Philipp Speckenmeyer & Guido Schryen, 2024. "The On-Demand Delivery Problem: Assignment of Orders to Warehouses and Couriers," Working Papers Dissertations 126, Paderborn University, Faculty of Business Administration and Economics.
    10. Abdul Aziz Khan Niazi & Tehmina Fiaz Qazi & Maryam Aziz & Abdul Basit & Ifra Aziz Khan Niazi, 2023. "Using the Binary Matrices for Modeling the Supply Chain Issues of Virtual Shops: An Evidence from Pakistan," Journal of Policy Research (JPR), Research Foundation for Humanity (RFH), vol. 9(2), pages 548-564.
    11. 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.
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