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Método Simplex×Descomposición de Benders×
CampoInvestigación operativaInvestigación operativa
FamiliaMachine learningMachine learning
Año de origen19471962
Autor originalGeorge DantzigJacques F. Benders
Tipoalgorithmalgorithm
Fuente seminalDantzig, G. B. (1963). Linear Programming and Extensions. Princeton University Press. DOI ↗Benders, J. F. (1962). Partitioning procedures for solving mixed-variables programming problems. Numerische Mathematik, 4(1), 238-252. DOI ↗
Aliassimplex algorithmcutting plane method, constraint generation
Relacionados43
ResumenThe 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.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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ScholarGateComparar métodos: Simplex Method · Benders Decomposition. Recuperado el 2026-06-15 de https://scholargate.app/es/compare