Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Algorithme de Wagner-Whitin× | Génération de colonnes (Dantzig-Wolfe)× | |
|---|---|---|
| Domaine | Recherche opérationnelle | Recherche opérationnelle |
| Famille | Machine learning | Machine learning |
| Année d'origine≠ | 1958 | 1960 |
| Auteur d'origine≠ | Harvey M. Wagner and Thomson M. Whitin | George B. Dantzig and Philip Wolfe |
| 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 ↗ | Dantzig, G. B., & Wolfe, P. (1960). Decomposition principle for linear programs. Operations Research, 8(1), 101-111. DOI ↗ |
| Alias | Wagner-Whitin lot-sizing, dynamic lot-sizing algorithm | Dantzig-Wolfe decomposition, column generation method |
| 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. | Column Generation, developed by George B. Dantzig and Philip Wolfe in 1960, is a powerful optimization technique for solving large-scale linear programming problems with special structure. Also known as Dantzig-Wolfe Decomposition, it decomposes the problem into a master problem (restricted to a subset of variables/columns) and a pricing subproblem (identifying new variables), iteratively improving the solution by introducing only relevant columns. |
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