Many optimal decision problems in scientific, engineering, and public sector applications
involve both discrete decisions and nonlinear system dynamics that affect the quality of the …

In this paper we review the relevant literature on mathematical optimization with logical
implications, ie, where constraints can be either active or disabled depending on logical …

Generalizing both mixed-integer linear optimization and convex optimization, mixed-integer
convex optimization possesses broad modeling power but has seen relatively few advances …

We present a unifying framework for generating extended formulations for the polyhedral
outer approximations used in algorithms for mixed-integer convex programming (MICP) …

We describe a computationally effective method for generating lift-and-project cuts for
convex mixed-integer nonlinear programs (MINLPs). The method relies on solving a …

In this thesis, we study mixed-integer convex optimization, or mixed-integer convex
programming (MICP), the class of optimization problems where one seeks to minimize a …

Disjunctive Cuts for Mixed Integer Nonlinear Programming Problems Page 1 Disjunctive Cuts
for Mixed Integer Nonlinear Programming Problems Pierre Bonami∗, Jeff Linderoth†, Andrea …

Strong branching is an effective branching technique that can significantly reduce the size of
the branch-and-bound tree for solving mixed integer nonlinear programming (MINLP) …

We develop and test linearization and parallelization schemes for convex mixed-integer
nonlinear programming. Several linearization approaches are proposed for LP/NLP based …

In this thesis we study selected topics in the field of Mixed Integer Programming (MIP), in
particular Mixed Integer Linear and Nonlinear Programming (MI (N) LP). We set a focus on …