Marcia Fampa, Federal University of Rio de Janeiro

Abstract

We address two classes of MINLP problems in this talk: convex MINLP and nonconvex MIQP. For the first, we discuss linearization algorithms and different strategies of adding linear cuts to strengthen the MILP master problem. We compare the outer approximation (OA) and the extended cutting plane (ECP) algorithms, and present a modification in ECP that aims at accelerating its convergence, still keeping the algorithm as a first order method. For MIQP, we discuss different strategies of convexifying an indefinite quadratic form, by decomposing it into the difference of two quadratic functions and applying linearization techniques for the remaining nonconvex quadratic.