Nonlinear Optimization

A multi-objective DIRECT algorithm for ship hull optimization
Issues on the use of a modified Bunch and Kaufman decomposition for large scale Newton’s equation

In this work, we deal with Truncated Newton methods for solving large scale (possibly nonconvex) unconstrained optimization problems. In particular,we consider the use of amodified Bunch and Kaufman factorization for solving the Newton equation, at each (outer) iteration of the method. The Bunch...
An algorithmic framework based on primitive directions and nonmonotone line searches for black-box optimization problems with integer variables
An active-set algorithmic framework for non-convex optimization problems over the simplex
Joaquim Judice

Prof. Joaquim Judice visited our department of Computer, Control, and Management
Engineering Antonio Ruberti (DIAG) of Sapienza University of Rome in the week 9th-15th
June 2019.

On Monday 10th, he gave a seminar entitled “Linear Complementarity Problems: Appli-
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An active set feasible method for large-scale minimization problems with bound constraints
Using a factored dual in augmented Lagrangian methods for semidefinite programming

In the context of augmented Lagrangian approaches for solving semidefinite programming problems, we investigate the possibility of eliminating the positive semidefinite constraint on the dual matrix by employing a factorization. Hints on how to deal with the resulting unconstrained maximization of...
Data and performance of an active-set truncated Newton method with non-monotone line search for bound-constrained optimization
A Two-Stage Active-Set Algorithm for Bound-Constrained Optimization
A fast active set block coordinate descent algorithm for ℓ1-regularized least squares