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خوارزمية فاغنر-ويتِن×توليد الأعمدة (دانزيغ-وولف)×الطريقة السيمبلكس×
المجالبحوث العملياتبحوث العملياتبحوث العمليات
العائلةMachine learningMachine learningMachine learning
سنة النشأة195819601947
صاحب الطريقةHarvey M. Wagner and Thomson M. WhitinGeorge B. Dantzig and Philip WolfeGeorge Dantzig
النوعalgorithmalgorithmalgorithm
المصدر التأسيسيWagner, 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 ↗
الأسماء البديلةWagner-Whitin lot-sizing, dynamic lot-sizing algorithmDantzig-Wolfe decomposition, column generation methodsimplex algorithm
ذات صلة334
الملخصThe 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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ScholarGateقارن الطرق: Wagner-Whitin Algorithm · Column Generation (Dantzig-Wolfe) · Simplex Method. استُرجع بتاريخ 2026-06-17 من https://scholargate.app/ar/compare