An infeasible active set method for convex problems with simple bounds

Karl Kunisch (kunischkfunigraz.ac.at)
Franz Rendl (franz.rendluni-klu.ac.at)

Abstract: A primal-dual active set method for convex quadratic problems with bound constraints is presented. Based on a guess on the active set, a primal-dual pair $(x,s)$ is computed that satisfies the first order optimality condition and the complementarity condition. If $(x,s)$ is not feasible, a new active set is determined, and the process is iterated. Sufficient conditions for the iterations to stop in a finite number of steps with an optimal solution are provided. Computational experience indicates that this approach often requires only a few (less than 10) iterations to find the optimal solution.

Keywords: active set method, convex programming

Category 1: Nonlinear Optimization (Bound-constrained Optimization )

Citation: SFB report, University of Graz, 2000

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Entry Submitted: 08/23/2000
Entry Last Modified: 08/23/2000

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