SIAM Journal on Optimization · 1996 · 128 citations · 11 references
ComputingComputer ScienceAlgorithmsOptimizationTheory Of ComputationApproximation AlgorithmsConvex AnalysisConvex OptimizationInteger ProgrammingLinear ProgrammingOptimization TheoryColumn GenerationComplexity AnalysisConvex Feasibility ProblemsCutting PlanesFeasibility ProblemsFinite TimePolynomial-time Approximation SchemeSeparation Theorems
We further analyze the convergence and the complexity of a dual column generation algorithm for solving general convex feasibility problems defined by a separation oracle. The oracle is called at an approximate analytic center of the set given by the intersection of the linear inequalities which are the previous answers of the oracle. We show that the algorithm converges in finite time and is in fact a fully polynomial approximation algorithm, provided that the feasible region has a nonempty interior.
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The Decomposition Algorithm for Linear Programs
George B. Dantzig, Philip Wolfe · Econometrica · 1961 · 749 citations
Path-Following Methods for Linear Programming
Clóvis C. Gonzaga · SIAM Review · 1992 · 341 citations