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Optimal Chaining of Vehicle Plans with Time Windows

Published 5 Jan 2024 in math.OC and cs.AI | (2401.02873v3)

Abstract: For solving problems from the domain of Mobility-on-Demand (MoD), we often need to connect vehicle plans into plans spanning longer time, a process we call plan chaining. As we show in this work, chaining of the plans can be used to reduce the size of MoD providers' fleet (fleet-sizing problem) but also to reduce the total driven distance by providing high-quality vehicle dispatching solutions in MoD systems. Recently, a solution that uses this principle has been proposed to solve the fleet-sizing problem. The method does not consider the time flexibility of the plans. Instead, plans are fixed in time and cannot be delayed. However, time flexibility is an essential property of all vehicle problems with time windows. This work presents a new plan chaining formulation that considers delays as allowed by the time windows and a solution method for solving it. Moreover, we prove that the proposed plan chaining method is optimal, and we analyze its complexity. Finally, we list some practical applications and perform a demonstration for one of them: a new heuristic vehicle dispatching method for solving the static dial-a-ride problem. The demonstration results show that our proposed method provides a better solution than the two heuristic baselines for the majority of instances that cannot be solved optimally. At the same time, our method does not have the largest computational time requirements compared to the baselines. Therefore, we conclude that the proposed optimal chaining method provides not only theoretically sound results but is also practically applicable.

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References (15)
  1. “Addressing the Minimum Fleet Problem in On-Demand Urban Mobility” In Nature 557.7706 Nature Publishing Group, 2018, pp. 534–538 DOI: 10.1038/s41586-018-0095-1
  2. “Towards Minimum Fleet for Ridesharing-Aware Mobility-on-Demand Systems” In IEEE INFOCOM 2021 - IEEE Conference on Computer Communications, 2021, pp. 1–10 DOI: 10.1109/INFOCOM42981.2021.9488862
  3. “Network-Flow-Based Efficient Vehicle Dispatch for City-Scale Ride-Hailing Systems” In IEEE Transactions on Intelligent Transportation Systems 23.6, 2022, pp. 5526–5538 DOI: 10.1109/TITS.2021.3054893
  4. “How Many Vehicles Do We Need? Fleet Sizing for Shared Autonomous Vehicles With Ridesharing” In IEEE Transactions on Intelligent Transportation Systems 23.9, 2022, pp. 14594–14607 DOI: 10.1109/TITS.2021.3130749
  5. “Quantifying the Benefits of Vehicle Pooling with Shareability Networks” In Proceedings of the National Academy of Sciences 111.37, 2014, pp. 13290–13294 DOI: 10.1073/pnas.1403657111
  6. “On-Demand High-Capacity Ride-Sharing via Dynamic Trip-Vehicle Assignment” In Proceedings of the National Academy of Sciences 114.3, 2017, pp. 462–467 DOI: 10.1073/pnas.1611675114
  7. “Multi-Objective Analysis of Ridesharing in Automated Mobility-on-Demand” In Robotics: Science and Systems XIV Robotics: Science and Systems Foundation, 2018 DOI: 10.15607/RSS.2018.XIV.039
  8. “Large-Scale Online Ridesharing: The Effect of Assignment Optimality on System Performance” In Journal of Intelligent Transportation Systems 0.0 Taylor & Francis, 2022, pp. 1–22 DOI: 10.1080/15472450.2022.2121651
  9. Ravindra K. Ahuja, Thomas L. Magnanti and James B. Orlin “Network Flows: Theory, Algorithms, and Applications” USA: Prentice-Hall, Inc., 1993
  10. “A Survey of Dial-a-Ride Problems: Literature Review and Recent Developments” In Transportation Research Part B: Methodological 111, 2018, pp. 395–421 DOI: 10.1016/j.trb.2018.02.001
  11. “Large-Scale Ridesharing DARP Instances Based on Real Travel Demand” arXiv, 2023 DOI: 10.48550/arXiv.2305.18859
  12. “A Heuristic Algorithm for the Multi-Vehicle Advance Request Dial-a-Ride Problem with Time Windows” In Transportation Research Part B: Methodological 20.3, 1986, pp. 243–257 DOI: 10.1016/0191-2615(86)90020-2
  13. “An Adaptive Large Neighborhood Search Heuristic for the Pickup and Delivery Problem with Time Windows” In Transportation Science 40.4, 2006, pp. 455–472 DOI: 10.1287/trsc.1050.0135
  14. “Hybrid Adaptive Large Neighborhood Search Algorithm for the Mixed Fleet Heterogeneous Dial-a-Ride Problem” In Journal of Heuristics 26.1, 2020, pp. 83–118 DOI: 10.1007/s10732-019-09424-x
  15. Gurobi Optimization, LLC “Gurobi Optimizer Reference Manual”, 2023

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