Solving a Distribution-Free Multi-Period Newsvendor Problem With Advance Purchase Discount via an Online Ordering Solution
In this paper, we study a distribution-free multi-period newsvendor problem with advance purchase discount (APD). In addition to the regular-order placed at the beginning of each period, a decision-maker (DM) can also commit to an advance-order from the upstream supplier and receive discounts. The g...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2023-06-01
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| Series: | SAGE Open |
| Online Access: | https://doi.org/10.1177/21582440231181101 |
| _version_ | 1797791807136858112 |
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| author | Rui Wang Xiao Yan Chuanjin Zhu |
| author_facet | Rui Wang Xiao Yan Chuanjin Zhu |
| author_sort | Rui Wang |
| collection | DOAJ |
| description | In this paper, we study a distribution-free multi-period newsvendor problem with advance purchase discount (APD). In addition to the regular-order placed at the beginning of each period, a decision-maker (DM) can also commit to an advance-order from the upstream supplier and receive discounts. The goal of the DM is to maximize total profits, and in this problem, the DM only has access to past demand data. To solve this problem, we apply an online method based on the theory of prediction and learning with expert advice to propose an explicit online ordering solution by using the fixed-stock policy as expert advice. With the properties of the gain function, we derive a theoretical result that guarantees, for any given advance-order quantity, the newsvendor’s cumulative gains achieved by the proposed online ordering solution converge to those from the best expert advice in hindsight for a sufficient large horizon. In addition, we extend the problem to the discrete case and obtain the corresponding explicit strategy and performance guarantee. Finally, numerical studies illustrate the effectiveness of the proposed solution, and the newsvendor’s total profits are comparable to the best expert advice. Sensitivity analysis also shows the robustness of the proposed solution. |
| first_indexed | 2024-03-13T02:24:03Z |
| format | Article |
| id | doaj.art-5e311a38827144119c0808e0fbe6265d |
| institution | Directory Open Access Journal |
| issn | 2158-2440 |
| language | English |
| last_indexed | 2024-03-13T02:24:03Z |
| publishDate | 2023-06-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | SAGE Open |
| spelling | doaj.art-5e311a38827144119c0808e0fbe6265d2023-06-30T06:33:36ZengSAGE PublishingSAGE Open2158-24402023-06-011310.1177/21582440231181101Solving a Distribution-Free Multi-Period Newsvendor Problem With Advance Purchase Discount via an Online Ordering SolutionRui Wang0Xiao Yan1Chuanjin Zhu2Chongqing University of Technology, ChinaSouthwestern University of Finance and Economics, Chengdu, ChinaChongqing Technology and Business University, ChinaIn this paper, we study a distribution-free multi-period newsvendor problem with advance purchase discount (APD). In addition to the regular-order placed at the beginning of each period, a decision-maker (DM) can also commit to an advance-order from the upstream supplier and receive discounts. The goal of the DM is to maximize total profits, and in this problem, the DM only has access to past demand data. To solve this problem, we apply an online method based on the theory of prediction and learning with expert advice to propose an explicit online ordering solution by using the fixed-stock policy as expert advice. With the properties of the gain function, we derive a theoretical result that guarantees, for any given advance-order quantity, the newsvendor’s cumulative gains achieved by the proposed online ordering solution converge to those from the best expert advice in hindsight for a sufficient large horizon. In addition, we extend the problem to the discrete case and obtain the corresponding explicit strategy and performance guarantee. Finally, numerical studies illustrate the effectiveness of the proposed solution, and the newsvendor’s total profits are comparable to the best expert advice. Sensitivity analysis also shows the robustness of the proposed solution.https://doi.org/10.1177/21582440231181101 |
| spellingShingle | Rui Wang Xiao Yan Chuanjin Zhu Solving a Distribution-Free Multi-Period Newsvendor Problem With Advance Purchase Discount via an Online Ordering Solution SAGE Open |
| title | Solving a Distribution-Free Multi-Period Newsvendor Problem With Advance Purchase Discount via an Online Ordering Solution |
| title_full | Solving a Distribution-Free Multi-Period Newsvendor Problem With Advance Purchase Discount via an Online Ordering Solution |
| title_fullStr | Solving a Distribution-Free Multi-Period Newsvendor Problem With Advance Purchase Discount via an Online Ordering Solution |
| title_full_unstemmed | Solving a Distribution-Free Multi-Period Newsvendor Problem With Advance Purchase Discount via an Online Ordering Solution |
| title_short | Solving a Distribution-Free Multi-Period Newsvendor Problem With Advance Purchase Discount via an Online Ordering Solution |
| title_sort | solving a distribution free multi period newsvendor problem with advance purchase discount via an online ordering solution |
| url | https://doi.org/10.1177/21582440231181101 |
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