Mixed Integer Nonlinear Programming

A fast branch-and-bound algorithm for non-convex quadratic integer optimization subject to linear constraints using ellipsoidal relaxations
Branching with hyperplanes in the criterion space: the frontier partitioner algorithm for biobjective integer programming

We present an algorithm for finding the complete Pareto frontier of biobjective integer programming problems. The method is based on the solution of a finite number of integer programs, each of them returning a Pareto optimal point. The feasible sets of the integer programs are built from the...
Continuous Optimization

Research in continuous optimization has been active at DIAG since its foundation. Early research was essentially devoted to the theory of exact penalization and to the development of algorithms for the solution of constrained nonlinear programming problems through unconstrained techniques....
Learning, Conjoint Analysis, and Binary Quadratic Optimization

In this talk, we present a learning approach to find good solutions for Binary Quadratic Programming. The proposed approach is based on learning a linear objective function which can then be used to optimize a linear binary program that provides a good feasible solution for the binary quadratic...
SpeeDP: an algorithm to compute SDP bounds for very large Max-Cut instances
A mathematical programming approach for the solution of the railway yield management problem
A fast branch-and-bound algorithm for non-convex quadratic integer optimization subject to linear constraints using ellipsoidal relaxations
An exact algorithm for nonconvex quadratic integer minimization using ellipsoidal relaxations
Computational Approaches to Max-Cut
MORE@DIAG: Marianna De Santis - Giorgio Grani

Titolo: "A Dual Step for Improving Alternating Augmented Lagrangian Methods for Semidefinite Programming"

Speaker: Marianna De Santis
(Joint work with Franz Rendl e Angelika Wiegele)

Abstract:
"It is well known that...