Near-optimal data-driven approximation schemes for joint pricing and inventory control models
Thesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2018.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2018
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| Online Access: | http://hdl.handle.net/1721.1/119336 |
| _version_ | 1826193709541097472 |
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| author | Qin, Hanzhang(Scientist in civil and environmental engineering)Massachusetts Institute of Technology |
| author2 | David Simchi-Levi. |
| author_facet | David Simchi-Levi. Qin, Hanzhang(Scientist in civil and environmental engineering)Massachusetts Institute of Technology |
| author_sort | Qin, Hanzhang(Scientist in civil and environmental engineering)Massachusetts Institute of Technology |
| collection | MIT |
| description | Thesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2018. |
| first_indexed | 2024-09-23T09:43:26Z |
| format | Thesis |
| id | mit-1721.1/119336 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T09:43:26Z |
| publishDate | 2018 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1193362023-01-20T13:19:56Z Near-optimal data-driven approximation schemes for joint pricing and inventory control models Qin, Hanzhang(Scientist in civil and environmental engineering)Massachusetts Institute of Technology David Simchi-Levi. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Civil and Environmental Engineering Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Civil and Environmental Engineering. Electrical Engineering and Computer Science. Thesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2018. Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018. Cataloged from PDF version of thesis. Includes bibliographical references (pages 95-96). The thesis studies the classical multi-period joint pricing and inventory control problem in a data-driven setting. In the problem, a retailer makes periodic decisions of the prices and inventory levels of an item that the retailer wishes to sell. The objective is to match the inventory level with a random demand that depends on the price in each period, while maximizing the expected profit over finite horizon. In reality, the demand functions or the distribution of the random noise are usually unavailable, whereas past demand data are relatively easy to collect. A novel data-driven nonparametric algorithm is proposed, which uses the past demand data to solve the joint pricing and inventory control problem, without assuming the parameters of the demand functions and the noise distributions are known. Explicit sample complexity bounds are given, on the number of data samples needed to guarantee a near-optimal profit. A simulation study suggests that the algorithm is efficient in practice. by Hanzhang Qin. S.M. in Transportation S.M. 2018-11-28T15:43:45Z 2018-11-28T15:43:45Z 2018 2018 Thesis http://hdl.handle.net/1721.1/119336 1065525187 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 96 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Civil and Environmental Engineering. Electrical Engineering and Computer Science. Qin, Hanzhang(Scientist in civil and environmental engineering)Massachusetts Institute of Technology Near-optimal data-driven approximation schemes for joint pricing and inventory control models |
| title | Near-optimal data-driven approximation schemes for joint pricing and inventory control models |
| title_full | Near-optimal data-driven approximation schemes for joint pricing and inventory control models |
| title_fullStr | Near-optimal data-driven approximation schemes for joint pricing and inventory control models |
| title_full_unstemmed | Near-optimal data-driven approximation schemes for joint pricing and inventory control models |
| title_short | Near-optimal data-driven approximation schemes for joint pricing and inventory control models |
| title_sort | near optimal data driven approximation schemes for joint pricing and inventory control models |
| topic | Civil and Environmental Engineering. Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/119336 |
| work_keys_str_mv | AT qinhanzhangscientistincivilandenvironmentalengineeringmassachusettsinstituteoftechnology nearoptimaldatadrivenapproximationschemesforjointpricingandinventorycontrolmodels |