On Policies for Single-Leg Revenue Management with Limited Demand Information
In this paper, we study the single-item revenue management problem, with no information given about the demand trajectory over time. When the item is sold through accepting/rejecting different fare classes, the tight competitive ratio for this problem has been established by Ball and Queyranne throu...
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| Eará dahkkit: | |
| Materiálatiipa: | Artihkal |
| Giella: | English |
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Institute for Operations Research and the Management Sciences (INFORMS)
2021
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| Liŋkkat: | https://hdl.handle.net/1721.1/133079 |
| _version_ | 1826193590828662784 |
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| author | Ma, Will Simchi-Levi, David Teo, Chung-Piaw |
| author2 | Massachusetts Institute of Technology. Institute for Data, Systems, and Society |
| author_facet | Massachusetts Institute of Technology. Institute for Data, Systems, and Society Ma, Will Simchi-Levi, David Teo, Chung-Piaw |
| author_sort | Ma, Will |
| collection | MIT |
| description | In this paper, we study the single-item revenue management problem, with no information given about the demand trajectory over time. When the item is sold through accepting/rejecting different fare classes, the tight competitive ratio for this problem has been established by Ball and Queyranne through booking limit policies, which raise the acceptance threshold as the remaining inventory dwindles. However, when the item is sold through dynamic pricing instead, there is the additional challenge that offering a low price may entice high-paying customers to substitute down. We show that despite this challenge, the same competitive ratio can still be achieved using a randomized dynamic pricing policy. Our policy incorporates the price-skimming technique originated by Eren and Maglaras, but importantly we show how the randomized price distribution should be stochastically increased as the remaining inventory dwindles. A key technical ingredient in our policy is a new “Valuation Tracking” subroutine, which tracks the possible values for the optimum, and follows the most “inventory-conservative” control, which maintains the desired competitive ratio. Finally, we demonstrate the empirical effectiveness of our policy in simulations, where its average-case performance surpasses all naive modifications of the existing policies. |
| first_indexed | 2024-09-23T09:41:32Z |
| format | Article |
| id | mit-1721.1/133079 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T09:41:32Z |
| publishDate | 2021 |
| publisher | Institute for Operations Research and the Management Sciences (INFORMS) |
| record_format | dspace |
| spelling | mit-1721.1/1330792024-06-06T13:40:37Z On Policies for Single-Leg Revenue Management with Limited Demand Information Ma, Will Simchi-Levi, David Teo, Chung-Piaw Massachusetts Institute of Technology. Institute for Data, Systems, and Society Massachusetts Institute of Technology. Department of Civil and Environmental Engineering Massachusetts Institute of Technology. Operations Research Center In this paper, we study the single-item revenue management problem, with no information given about the demand trajectory over time. When the item is sold through accepting/rejecting different fare classes, the tight competitive ratio for this problem has been established by Ball and Queyranne through booking limit policies, which raise the acceptance threshold as the remaining inventory dwindles. However, when the item is sold through dynamic pricing instead, there is the additional challenge that offering a low price may entice high-paying customers to substitute down. We show that despite this challenge, the same competitive ratio can still be achieved using a randomized dynamic pricing policy. Our policy incorporates the price-skimming technique originated by Eren and Maglaras, but importantly we show how the randomized price distribution should be stochastically increased as the remaining inventory dwindles. A key technical ingredient in our policy is a new “Valuation Tracking” subroutine, which tracks the possible values for the optimum, and follows the most “inventory-conservative” control, which maintains the desired competitive ratio. Finally, we demonstrate the empirical effectiveness of our policy in simulations, where its average-case performance surpasses all naive modifications of the existing policies. 2021-10-25T14:17:55Z 2021-10-25T14:17:55Z 2020-12 2018-10 2021-10-21T17:00:33Z Article http://purl.org/eprint/type/JournalArticle 0030-364X 1526-5463 https://hdl.handle.net/1721.1/133079 Will Ma, David Simchi-Levi, Chung-Piaw Teo (2020) On Policies for Single-Leg Revenue Management with Limited Demand Information. Operations Research 69(1):207-226. en 10.1287/OPRE.2020.2048 Operations Research Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Institute for Operations Research and the Management Sciences (INFORMS) arXiv |
| spellingShingle | Ma, Will Simchi-Levi, David Teo, Chung-Piaw On Policies for Single-Leg Revenue Management with Limited Demand Information |
| title | On Policies for Single-Leg Revenue Management with Limited Demand Information |
| title_full | On Policies for Single-Leg Revenue Management with Limited Demand Information |
| title_fullStr | On Policies for Single-Leg Revenue Management with Limited Demand Information |
| title_full_unstemmed | On Policies for Single-Leg Revenue Management with Limited Demand Information |
| title_short | On Policies for Single-Leg Revenue Management with Limited Demand Information |
| title_sort | on policies for single leg revenue management with limited demand information |
| url | https://hdl.handle.net/1721.1/133079 |
| work_keys_str_mv | AT mawill onpoliciesforsinglelegrevenuemanagementwithlimiteddemandinformation AT simchilevidavid onpoliciesforsinglelegrevenuemanagementwithlimiteddemandinformation AT teochungpiaw onpoliciesforsinglelegrevenuemanagementwithlimiteddemandinformation |