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Kolumngenerering (Dantzig-Wolfe)×Benders dekomposition×
ÄmnesområdeOperationsanalysOperationsanalys
FamiljMachine learningMachine learning
Ursprungsår19601962
UpphovspersonGeorge B. Dantzig and Philip WolfeJacques F. Benders
Typalgorithmalgorithm
UrsprungskällaDantzig, G. B., & Wolfe, P. (1960). Decomposition principle for linear programs. Operations Research, 8(1), 101-111. DOI ↗Benders, J. F. (1962). Partitioning procedures for solving mixed-variables programming problems. Numerische Mathematik, 4(1), 238-252. DOI ↗
AliasDantzig-Wolfe decomposition, column generation methodcutting plane method, constraint generation
Närliggande33
SammanfattningColumn 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.Benders Decomposition, introduced by Jacques F. Benders in 1962, is a powerful algorithmic framework for solving large-scale mixed-integer programming (MIP) problems. It decomposes the problem into a master problem (controlling complicating variables) and subproblems (handling remaining variables), using cutting planes generated from subproblem dual information to iteratively tighten the master problem.
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ScholarGateJämför metoder: Column Generation (Dantzig-Wolfe) · Benders Decomposition. Hämtad 2026-06-18 från https://scholargate.app/sv/compare