Dynamic prediction-based relocation policies in one-way station-based carsharing systems with complete journey reservations

Martin Repoux, Mor Kaspi, Burak Boyacı and Nikolas Geroliminis

Transportation Research Part B: Methodological, 2019, vol. 130, issue C, 82-104

Abstract: In this paper, we study the operations of a one-way station-based carsharing system implementing a complete journey reservation policy. We consider the percentage of served demand as a primary performance measure and analyze the effect of several dynamic staff-based relocation policies. Specifically, we introduce a new proactive relocation policy based on Markov chain dynamics that utilizes reservation information to better predict the future states of the stations. This policy is compared to a state-of-the art staff-based relocation policy and a centralistic relocation model assuming full knowledge of the demand. Numerical results from a real-world implementation and a simulation analysis demonstrate the positive impact of dynamic relocations and highlight the improvement in performance obtained with the proposed proactive relocation policy.

Keywords: Carsharing; Simulation; Markov chain; Prediction; Operations (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (10)

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DOI: 10.1016/j.trb.2019.10.004

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