File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1111/poms.13453
- Scopus: eid_2-s2.0-85112597249
- WOS: WOS:000683062200001
- Find via
Supplementary
- Citations:
- Appears in Collections:
Article: Mechanism Design for Stochastic Dynamic Parking Resource Allocation
Title | Mechanism Design for Stochastic Dynamic Parking Resource Allocation |
---|---|
Authors | |
Issue Date | 2021 |
Publisher | Wiley-Blackwell Publishing, Inc.. The Journal's web site is located at http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1937-5956 |
Citation | Production and Operations Management, 2021, v. 30 n. 10, p. 3615-3634 How to Cite? |
Abstract | In this paper, we study a parking management problem where an operator manages a publicly owned parking service system with unknown parking demand. Assuming that the operator has perfect information, we first formulate the operator's problem as a stochastic dynamic programming problem, and to overcome the curse of dimensionality, we resort to approximate dynamic programming for solving it. However, in practice, some information that is essential for centralized management is usually privately known, which provides incentives for strategic behaviors of drivers and could lead to suboptimal system performance. We design a two-step mechanism and prove that, in step 1, drivers’ choices of whether or not to enter the managed system following the approximate optimal solution satisfy Bayesian-Nash equilibrium (BNE), and in step 2, that truthful reporting is a dominant strategy for all drivers under any circumstance. We investigate the properties of the resulting equilibria, and further modify the mechanism to ensure that the desired approximate system optimum solution is the only resulting BNE. Numerical examples show that the mechanism design not only enhances the average system performance but also increases the system robustness. |
Persistent Identifier | http://hdl.handle.net/10722/310084 |
ISSN | 2023 Impact Factor: 4.8 2023 SCImago Journal Rankings: 3.035 |
ISI Accession Number ID |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yang, J | - |
dc.contributor.author | He, F | - |
dc.contributor.author | Lin, X | - |
dc.contributor.author | Shen, ZM | - |
dc.date.accessioned | 2022-01-24T02:23:35Z | - |
dc.date.available | 2022-01-24T02:23:35Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | Production and Operations Management, 2021, v. 30 n. 10, p. 3615-3634 | - |
dc.identifier.issn | 1059-1478 | - |
dc.identifier.uri | http://hdl.handle.net/10722/310084 | - |
dc.description.abstract | In this paper, we study a parking management problem where an operator manages a publicly owned parking service system with unknown parking demand. Assuming that the operator has perfect information, we first formulate the operator's problem as a stochastic dynamic programming problem, and to overcome the curse of dimensionality, we resort to approximate dynamic programming for solving it. However, in practice, some information that is essential for centralized management is usually privately known, which provides incentives for strategic behaviors of drivers and could lead to suboptimal system performance. We design a two-step mechanism and prove that, in step 1, drivers’ choices of whether or not to enter the managed system following the approximate optimal solution satisfy Bayesian-Nash equilibrium (BNE), and in step 2, that truthful reporting is a dominant strategy for all drivers under any circumstance. We investigate the properties of the resulting equilibria, and further modify the mechanism to ensure that the desired approximate system optimum solution is the only resulting BNE. Numerical examples show that the mechanism design not only enhances the average system performance but also increases the system robustness. | - |
dc.language | eng | - |
dc.publisher | Wiley-Blackwell Publishing, Inc.. The Journal's web site is located at http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1937-5956 | - |
dc.relation.ispartof | Production and Operations Management | - |
dc.rights | Submitted (preprint) Version This is the pre-peer reviewed version of the following article: [FULL CITE], which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. Accepted (peer-reviewed) Version This is the peer reviewed version of the following article: [FULL CITE], which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. | - |
dc.title | Mechanism Design for Stochastic Dynamic Parking Resource Allocation | - |
dc.type | Article | - |
dc.identifier.email | Shen, ZM: maxshen@hku.hk | - |
dc.identifier.authority | Shen, ZM=rp02779 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1111/poms.13453 | - |
dc.identifier.scopus | eid_2-s2.0-85112597249 | - |
dc.identifier.hkuros | 331476 | - |
dc.identifier.volume | 30 | - |
dc.identifier.issue | 10 | - |
dc.identifier.spage | 3615 | - |
dc.identifier.epage | 3634 | - |
dc.identifier.isi | WOS:000683062200001 | - |
dc.publisher.place | United States | - |