方法对比
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| Wagner-Whitin 算法× | 列生成算法 (Dantzig-Wolfe)× | 单纯形法× | |
|---|---|---|---|
| 领域 | 运筹学 | 运筹学 | 运筹学 |
| 方法族 | Machine learning | Machine learning | Machine learning |
| 起源年份≠ | 1958 | 1960 | 1947 |
| 提出者≠ | Harvey M. Wagner and Thomson M. Whitin | George B. Dantzig and Philip Wolfe | George Dantzig |
| 类型 | algorithm | algorithm | algorithm |
| 开创性文献≠ | 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 ↗ | Dantzig, G. B. (1963). Linear Programming and Extensions. Princeton University Press. DOI ↗ |
| 别名≠ | Wagner-Whitin lot-sizing, dynamic lot-sizing algorithm | Dantzig-Wolfe decomposition, column generation method | simplex algorithm |
| 相关≠ | 3 | 3 | 4 |
| 摘要≠ | 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. | The Simplex Method, developed by George Dantzig in 1947, is a foundational algorithm for solving linear programming problems. It systematically explores vertices of the feasible region to find the optimal solution where the objective function is maximized or minimized subject to linear constraints. |
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