A Study of the Difference-of-Convex Approach for Solving Linear Programs with Complementarity Constraints



This work studies the difference-of-convex (DC) penalty formulations and the associated difference-of-convex algorithm (DCA) for computing stationary solutions of linear programs with complementarity constraints (LPCCs). We focus on two such formulations and establish connections between their stationary solutions and those of the LPCC. Improvements of the DCA are proposed to remedy some drawbacks in a straightforward adaptation of the DCA to these formulations. Extensive numerical results, including comparisons with an existing nonlinear programming solver and the mixed-integer formulation, are presented to elucidate the effectiveness of the overall DC approach.



Date: Sep 05, 2018 at 16:30 h
Venue: Beauchef 851, Torre Norte, Piso 7, Sala de Seminarios CMM John Von Neumann.
Speaker: Francisco Jara-Moroni
Affiliation: Northwestern University
Coordinator: Profesores Juan Peypouquet & Salvador Flores

Posted on Aug 23, 2018 in Optimization and Equilibrium, Seminars