Admission and Pricing Optimization of On-Street Parking with Delivery Bays

Benjamin Legros and Jan C. Fransoo
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Benjamin Legros: Métis Lab EM Normandie - EM Normandie - École de Management de Normandie = EM Normandie Business School
Jan C. Fransoo: TiSEM - Tilburg School of Economics and Management - Tilburg University [Netherlands]

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Abstract: We analyze a parking lot, modeled as a loss queue, with passenger and delivery vehicles. The arrival process of delivery vehicles is exogenous, while that of passenger vehicles is a function of the parking price rate and accessibility. The aim of the parking operator is to maximize the revenue generated from passenger vehicles while providing a sufficient service level for delivery vehicles, in terms of their probability to find an available parking spot. Two levels of control are exercised: pricing and admission. From a Markov decision process approach, we prove that the optimal policy is a state-dependent reservation threshold policy that randomizes in at most one state. When some parking spots should be reserved for delivery vehicles, the price rate is selected to saturate the service level constraint, whereas when it is optimal not to restrict the parking lot accessibility, the price can also be selected as the unique local maximum of the revenue or to incentivize all potential passenger vehicles to arrive. Pricing should be used as a primary tool to control the flow of passenger vehicles. In complement, admission control is exercised with a limited use of reservation only when the service level guarantee for delivery vehicles is high. \textcopyright 2023 Elsevier B.V.

Keywords: (O) transportation; (O) Transportation; Arrival process; Costs; Delivery and passenger vehicles; Delivery vehicle; Economics; Markov processes; On-street parking; Optimisations; Parking lot; Parking lots; Parking spot; Passengers vehicles; Pricing; Queue; Service levels; Vehicles (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

Published in European Journal of Operational Research, 2024, 312 (1), pp.138--149. ⟨10.1016/j.ejor.2023.07.001⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04432404

DOI: 10.1016/j.ejor.2023.07.001

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