Revenue Management of Reusable Resources with Advanced Reservations
We consider a revenue management problem wherein the seller is endowed with a single type resource with a finite capacity and the resource can be repeatedly used to serve customers. There are multiple classes of customers arriving according to a multi-class Poisson process. Each customer, upon arriv...
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| 格式: | 文件 |
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Wiley
2020
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| 在线阅读: | https://hdl.handle.net/1721.1/126893 |
| _version_ | 1826197408721141760 |
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| author | Chen, Yiwei Levi, Retsef Shi, Cong |
| author2 | Sloan School of Management |
| author_facet | Sloan School of Management Chen, Yiwei Levi, Retsef Shi, Cong |
| author_sort | Chen, Yiwei |
| collection | MIT |
| description | We consider a revenue management problem wherein the seller is endowed with a single type resource with a finite capacity and the resource can be repeatedly used to serve customers. There are multiple classes of customers arriving according to a multi-class Poisson process. Each customer, upon arrival, submits a service request that specifies his service start time and end time. Our model allows customer advanced reservation times and services times in each class to be arbitrarily distributed and correlated. Upon arrival of each customer, the seller must instantaneously decide whether to accept this customer's service request. A customer whose request is denied leaves the system. A customer whose request is accepted is allocated with a specific item of the resource at his service start time. The resource unit occupied by a customer becomes available to other customers after serving this customer. The seller aims to design an admission control policy that maximizes her expected long-run average revenue. We propose a policy called the ε-perturbation class selection policy (ε-CSP), based on the optimal solution in the fluid setting wherein customers are infinitesimal and customer arrival processes are deterministic, under the restriction that the seller can utilize at most (1 − ε) of her capacity for any ε ∈ (0, 1). We prove that the ε-CSP is near-optimal. More precisely, we develop an upper bound of the performance loss of the ε-CSP relative to the seller's optimal revenue, and show that it converges to zero with a square-root convergence rate in the asymptotic regime wherein the arrival rates and the capacity grow up proportionally and the capacity buffer level ε decays to zero. |
| first_indexed | 2024-09-23T10:47:15Z |
| format | Article |
| id | mit-1721.1/126893 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T10:47:15Z |
| publishDate | 2020 |
| publisher | Wiley |
| record_format | dspace |
| spelling | mit-1721.1/1268932022-09-30T23:02:31Z Revenue Management of Reusable Resources with Advanced Reservations Chen, Yiwei Levi, Retsef Shi, Cong Sloan School of Management We consider a revenue management problem wherein the seller is endowed with a single type resource with a finite capacity and the resource can be repeatedly used to serve customers. There are multiple classes of customers arriving according to a multi-class Poisson process. Each customer, upon arrival, submits a service request that specifies his service start time and end time. Our model allows customer advanced reservation times and services times in each class to be arbitrarily distributed and correlated. Upon arrival of each customer, the seller must instantaneously decide whether to accept this customer's service request. A customer whose request is denied leaves the system. A customer whose request is accepted is allocated with a specific item of the resource at his service start time. The resource unit occupied by a customer becomes available to other customers after serving this customer. The seller aims to design an admission control policy that maximizes her expected long-run average revenue. We propose a policy called the ε-perturbation class selection policy (ε-CSP), based on the optimal solution in the fluid setting wherein customers are infinitesimal and customer arrival processes are deterministic, under the restriction that the seller can utilize at most (1 − ε) of her capacity for any ε ∈ (0, 1). We prove that the ε-CSP is near-optimal. More precisely, we develop an upper bound of the performance loss of the ε-CSP relative to the seller's optimal revenue, and show that it converges to zero with a square-root convergence rate in the asymptotic regime wherein the arrival rates and the capacity grow up proportionally and the capacity buffer level ε decays to zero. NSF (Grants DMS-0732175 and CMMI-0846554) Air Force Office of Scientific Research (Award FA9550-08-1- 0369) 2020-09-01T22:59:18Z 2020-09-01T22:59:18Z 2017-01 2015-05 2019-02-21T18:47:19Z Article http://purl.org/eprint/type/JournalArticle 1059-1478 https://hdl.handle.net/1721.1/126893 Chen, Yiwei et al. “Revenue Management of Reusable Resources with Advanced Reservations.” Production and Operations Management 26, 5 (January 2017): 836–859 © 2016 Production and Operations Management Society http://dx.doi.org/10.1111/poms.12672 Production and Operations Management Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Wiley Other repository |
| spellingShingle | Chen, Yiwei Levi, Retsef Shi, Cong Revenue Management of Reusable Resources with Advanced Reservations |
| title | Revenue Management of Reusable Resources with Advanced Reservations |
| title_full | Revenue Management of Reusable Resources with Advanced Reservations |
| title_fullStr | Revenue Management of Reusable Resources with Advanced Reservations |
| title_full_unstemmed | Revenue Management of Reusable Resources with Advanced Reservations |
| title_short | Revenue Management of Reusable Resources with Advanced Reservations |
| title_sort | revenue management of reusable resources with advanced reservations |
| url | https://hdl.handle.net/1721.1/126893 |
| work_keys_str_mv | AT chenyiwei revenuemanagementofreusableresourceswithadvancedreservations AT leviretsef revenuemanagementofreusableresourceswithadvancedreservations AT shicong revenuemanagementofreusableresourceswithadvancedreservations |