Enregistré dans:
| Auteurs principaux: | , , , |
|---|---|
| Format: | Preprint |
| Publié: |
2024
|
| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2410.18571 |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866912084233551872 |
|---|---|
| author | González-Díaz, Julio González-Rueda, Ángel M. Llana-García, Irene Rodríguez-Veiga, Jorge |
| author_facet | González-Díaz, Julio González-Rueda, Ángel M. Llana-García, Irene Rodríguez-Veiga, Jorge |
| contents | We study the problem of stock replenishment and transshipment in the retail industry. We develop a model that can accommodate different policies, including centralized redistribution (replenishment) and decentralized redistribution (lateral transshipments), allowing for direct comparisons between them. We present a numeric analysis in which the benchmark instances stem from the collaboration with a high-end clothing retail company. The underlying model, as usually in the field, is a large-scale mixed-integer linear programming problem. We develop a specific algorithmic procedure to solve this MILP problem and compare its performance with the direct solution via state-of-the-art solvers. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_18571 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Optimal policies for stock redistribution in a retail network: Mathematical modeling and algorithmic solution González-Díaz, Julio González-Rueda, Ángel M. Llana-García, Irene Rodríguez-Veiga, Jorge Optimization and Control We study the problem of stock replenishment and transshipment in the retail industry. We develop a model that can accommodate different policies, including centralized redistribution (replenishment) and decentralized redistribution (lateral transshipments), allowing for direct comparisons between them. We present a numeric analysis in which the benchmark instances stem from the collaboration with a high-end clothing retail company. The underlying model, as usually in the field, is a large-scale mixed-integer linear programming problem. We develop a specific algorithmic procedure to solve this MILP problem and compare its performance with the direct solution via state-of-the-art solvers. |
| title | Optimal policies for stock redistribution in a retail network: Mathematical modeling and algorithmic solution |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2410.18571 |