On reduced convex QP formulations of monotone LCPs
Techniques for transforming convex quadratic programs (QPs) into monotone linear complementarity problems (LCPa) and vice versa, are well known, We describre 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.
convex quadratic programming monotone linens complementarity problems karush-kuhn-tucker conditions