Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Algorithme de Wagner-Whitin× | Décomposition de Benders× | |
|---|---|---|
| Domaine | Recherche opérationnelle | Recherche opérationnelle |
| Famille | Machine learning | Machine learning |
| Année d'origine≠ | 1958 | 1962 |
| Auteur d'origine≠ | Harvey M. Wagner and Thomson M. Whitin | Jacques F. Benders |
| Type | algorithm | algorithm |
| Source fondatrice≠ | Wagner, H. M., & Whitin, T. M. (1958). Dynamic version of the economic lot size model. Management Science, 5(1), 89-96. DOI ↗ | Benders, J. F. (1962). Partitioning procedures for solving mixed-variables programming problems. Numerische Mathematik, 4(1), 238-252. DOI ↗ |
| Alias | Wagner-Whitin lot-sizing, dynamic lot-sizing algorithm | cutting plane method, constraint generation |
| Apparentées | 3 | 3 |
| Résumé≠ | The Wagner-Whitin Algorithm, introduced by Harvey M. Wagner and Thomson M. Whitin in 1958, is a dynamic programming solution to the capacitated lot-sizing problem. It determines optimal production quantities over multiple periods to minimize the total cost of production setup and inventory holding while meeting deterministic demand. | Benders Decomposition, introduced by Jacques F. Benders in 1962, is a powerful algorithmic framework for solving large-scale mixed-integer programming (MIP) problems. It decomposes the problem into a master problem (controlling complicating variables) and subproblems (handling remaining variables), using cutting planes generated from subproblem dual information to iteratively tighten the master problem. |
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