On reduced QP formulations of monotone LCP problems
Stephen J. Wright (swrightcs.wisc.edu)
Abstract: Techniques for transforming convex quadratic programs (QPs) into monotone linear complementarity problems (LCPs) and vice versa are well known. We describe a class of LCPs for which a reduced QP formulation---one that has fewer constraints than the ``standard'' QP formulation---is available. We mention several instances of this class, including the known case in which the coefficient matrix in the LCP is symmetric.
Keywords: Monotone Linear Complementarity Problems, Convex Quadratic Programming, Karush-Kuhn-Tucker Conditions
Category 1: Complementarity and Variational Inequalities
Category 2: Nonlinear Optimization (Quadratic Programming )
Citation: Preprint P808-0400, MCS Division, Argonne National Laboratory, April, 2000. Published in Mathematical Programming, Series A, 90 (2001), pp. 459--473.
Entry Submitted: 08/18/2000
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