Promotion Optimization for Multiple Items in Supermarkets
Promotions are a critical decision for supermarket managers, who must decide the price promotions for a large number of items. Retailers often use promotions to boost the sales of the different items by leveraging the cross-item effects. We formulate the promotion optimization problem for multiple i...
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| Other Authors: | |
| Format: | Article |
| Language: | English |
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Institute for Operations Research and the Management Sciences (INFORMS)
2021
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| Online Access: | https://hdl.handle.net/1721.1/130364 |
| _version_ | 1826204795654897664 |
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| author | Kalas, Jeremy J. Perakis, Georgia |
| author2 | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
| author_facet | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Kalas, Jeremy J. Perakis, Georgia |
| author_sort | Kalas, Jeremy J. |
| collection | MIT |
| description | Promotions are a critical decision for supermarket managers, who must decide the price promotions for a large number of items. Retailers often use promotions to boost the sales of the different items by leveraging the cross-item effects. We formulate the promotion optimization problem for multiple items as a nonlinear integer program. Our formulation includes several business rules as constraints. Our demand models can be estimated from data and capture the postpromotion dip effect and cross-item effects (substitution and complementarity). Because demand functions are typically nonlinear, the exact formulation is intractable. To address this issue, we propose a general class of integer programming approximations. For demand models with additive cross-item effects, we prove that it is sufficient to account for unilateral and pairwise contributions and derive parametric bounds on the performance of the approximation. We also show that the unconstrained problem can be solved efficiently via a linear program when items are substitutable and the price set has two values. For more general cases, we develop efficient rounding schemes to obtain an integer solution. We conclude by testing our method on realistic instances and convey the potential practical impact for retailers. |
| first_indexed | 2024-09-23T13:01:31Z |
| format | Article |
| id | mit-1721.1/130364 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T13:01:31Z |
| publishDate | 2021 |
| publisher | Institute for Operations Research and the Management Sciences (INFORMS) |
| record_format | dspace |
| spelling | mit-1721.1/1303642022-10-01T12:36:40Z Promotion Optimization for Multiple Items in Supermarkets Kalas, Jeremy J. Perakis, Georgia Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Sloan School of Management Promotions are a critical decision for supermarket managers, who must decide the price promotions for a large number of items. Retailers often use promotions to boost the sales of the different items by leveraging the cross-item effects. We formulate the promotion optimization problem for multiple items as a nonlinear integer program. Our formulation includes several business rules as constraints. Our demand models can be estimated from data and capture the postpromotion dip effect and cross-item effects (substitution and complementarity). Because demand functions are typically nonlinear, the exact formulation is intractable. To address this issue, we propose a general class of integer programming approximations. For demand models with additive cross-item effects, we prove that it is sufficient to account for unilateral and pairwise contributions and derive parametric bounds on the performance of the approximation. We also show that the unconstrained problem can be solved efficiently via a linear program when items are substitutable and the price set has two values. For more general cases, we develop efficient rounding schemes to obtain an integer solution. We conclude by testing our method on realistic instances and convey the potential practical impact for retailers. National Science Foundation (U.S.) (Grant CMMI-1162034) 2021-04-05T15:21:07Z 2021-04-05T15:21:07Z 2020-06 2017-10 2021-04-05T14:16:47Z Article http://purl.org/eprint/type/JournalArticle 0025-1909 https://hdl.handle.net/1721.1/130364 Duguay, Raphael et al. “Promotion Optimization for Multiple Items in Supermarkets.” Management Science (June 2020) © 2020 The Author(s) en 10.1287/MNSC.2020.3641 Management Science 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) SSRN |
| spellingShingle | Kalas, Jeremy J. Perakis, Georgia Promotion Optimization for Multiple Items in Supermarkets |
| title | Promotion Optimization for Multiple Items in Supermarkets |
| title_full | Promotion Optimization for Multiple Items in Supermarkets |
| title_fullStr | Promotion Optimization for Multiple Items in Supermarkets |
| title_full_unstemmed | Promotion Optimization for Multiple Items in Supermarkets |
| title_short | Promotion Optimization for Multiple Items in Supermarkets |
| title_sort | promotion optimization for multiple items in supermarkets |
| url | https://hdl.handle.net/1721.1/130364 |
| work_keys_str_mv | AT kalasjeremyj promotionoptimizationformultipleitemsinsupermarkets AT perakisgeorgia promotionoptimizationformultipleitemsinsupermarkets |