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Algoritmus Wagnera-Whitina×Generování sloupců (Dantzig-Wolfe)×Simplexová metoda×
OborOperační výzkumOperační výzkumOperační výzkum
RodinaMachine learningMachine learningMachine learning
Rok vzniku195819601947
TvůrceHarvey M. Wagner and Thomson M. WhitinGeorge B. Dantzig and Philip WolfeGeorge Dantzig
Typalgorithmalgorithmalgorithm
Původní zdrojWagner, 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 ↗
Další názvyWagner-Whitin lot-sizing, dynamic lot-sizing algorithmDantzig-Wolfe decomposition, column generation methodsimplex algorithm
Příbuzné334
ShrnutíThe 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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ScholarGatePorovnat metody: Wagner-Whitin Algorithm · Column Generation (Dantzig-Wolfe) · Simplex Method. Získáno 2026-06-17 z https://scholargate.app/cs/compare