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	Algorytm Wagnera-Whitina	Generowanie kolumn (Dantzig-Wolfe)	Metoda Simplex
Dziedzina	Badania operacyjne	Badania operacyjne	Badania operacyjne
Rodzina	Machine learning	Machine learning	Machine learning
Rok powstania	1958	1960	1947
Twórca	Harvey M. Wagner and Thomson M. Whitin	George B. Dantzig and Philip Wolfe	George Dantzig
Typ	algorithm	algorithm	algorithm
Źródło pierwotne	Wagner, H. M., & Whitin, T. M. (1958). Dynamic version of the economic lot size model. Management Science, 5(1), 89-96.	Dantzig, G. B., & Wolfe, P. (1960). Decomposition principle for linear programs. Operations Research, 8(1), 101-111.	Dantzig, G. B. (1963). Linear Programming and Extensions. Princeton University Press.
Inne nazwy	Wagner-Whitin lot-sizing, dynamic lot-sizing algorithm	Dantzig-Wolfe decomposition, column generation method	simplex algorithm
Pokrewne	3	3	4
Podsumowanie	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.