Nonlinear Optimization

An algorithmic framework based on primitive directions and nonmonotone line searches for black-box optimization problems with integer variables
An implicit filtering algorithm for derivative-free multiobjective optimization with box constraints

This paper is concerned with the definition of new derivative-free methods for box constrained multiobjective optimization. The method that we propose is a non-trivial extension of the well-known implicit filtering algorithm to the multiobjective case. Global convergence results are stated under...
A derivative-free approach to constrained multiobjective nonsmooth optimization
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-
...
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