Giampaolo Liuzzi

Nonlinear Derivative-free Constrained Optimization with a Mixed Penalty-Logarithmic Barrier Approach and Direct Search

  • Andrea Brilli
  • Ana Luisa Custódio
  • Giampaolo Liuzzi
  • Everton Silva
    • Categories Constrained Nonlinear Optimization Tags , , ,

    In this work, we propose the joint use of a mixed penalty-logarithmic barrier approach and generating set search, for addressing nonlinearly constrained derivative-free optimization problems. A merit function is considered, wherein the set of inequality constraints is divided into two groups: one treated with a logarithmic barrier approach, and another, along with the equality constraints, … Read more

    Complexity results and active-set identification of a derivative-free method for bound-constrained problems

  • Andrea Brilli
  • Andrea Cristofari
  • Giampaolo Liuzzi
  • Stefano Lucidi
    • Categories Bound-constrained Optimization, Nonlinear Optimization Tags , ,

    In this paper, we analyze a derivative-free line search method designed for bound-constrained problems. Our analysis demonstrates that this method exhibits a worst-case complexity comparable to other derivative-free methods for unconstrained and linearly constrained problems. In particular, when minimizing a function with $n$ variables, we prove that at most ${\cal O}(n\epsilon^{-2})$ iterations are needed to … Read more

    An augmented Lagrangian method exploiting an active-set strategy and second-order information

  • Andrea Cristofari
  • Gianni Di Pillo
  • Giampaolo Liuzzi
  • Stefano Lucidi
    • Categories Constrained Nonlinear Optimization Tags , , ,

    In this paper, we consider nonlinear optimization problems with nonlinear equality constraints and bound constraints on the variables. For the solution of such problems, many augmented Lagrangian methods have been defined in the literature. Here, we propose to modify one of these algorithms, namely ALGENCAN by Andreani et al., in such a way to incorporate … Read more

    Computing mixed strategies equilibria in presence of switching costs by the solution of nonconvex QP problems

  • Giampaolo Liuzzi
  • Marco Locatelli
  • Veronica Piccialli
  • Stefan Rass
    • Categories Game Theory, Global Optimization Applications, Quadratic Programming

    In this paper we address a game theory problem arising in the context of network security. In traditional game theory problems, given a defender and an attacker, one searches for mixed strategies which minimize a linear payoff functional. In the problem addressed in this paper an additional quadratic term is added to the minimization problem. … Read more

    Trust-region methods for the derivative-free optimization of nonsmooth black-box functions

  • Giampaolo Liuzzi
  • Stefano Lucidi
  • Francesco Rinaldi
  • Luis Nunes Vicente
    • Categories Applications - Science and Engineering, Nonlinear Optimization, Nonsmooth Optimization Tags , , ,

    In this paper we study the minimization of a nonsmooth black-box type function, without assuming any access to derivatives or generalized derivatives and without any knowledge about the analytical origin of the function nonsmoothness. Directional methods have been derived for such problems but to our knowledge no model-based method like a trust-region one has yet … Read more

    An algorithmic framework based on primitive directions and nonmonotone line searches for black box problems with integer variables

  • Giampaolo Liuzzi
  • Stefano Lucidi
  • Francesco Rinaldi
    • Categories Integer Programming, Optimization Software and Modeling Systems

    In this paper, we develop a new algorithmic framework that handles black box problems with integer variables. The strategy included in the framework makes use of specific search directions (so called primitive directions) and a suitably developed nonmonotone line search, thus guaranteeing a high level of freedom when exploring the integer lattice. We first describe … Read more

    A new branch-and-bound algorithm for standard quadratic programming problems

  • Giampaolo Liuzzi
  • Marco Locatelli
  • Veronica Piccialli
    • Categories Global Optimization, Quadratic Programming

    In this paper we propose convex and LP bounds for Standard Quadratic Programming (StQP) problems and employ them within a branch-and-bound approach. We first compare different bounding strategies for StQPs in terms both of the quality of the bound and of the computation times. It turns out that the polyhedral bounding strategy is the best … Read more

    A DERIVATIVE-FREE APPROACH TO CONSTRAINED MULTIOBJECTIVE NONSMOOTH OPTIMIZATION

  • Giampaolo Liuzzi
  • Stefano Lucidi
  • Francesco Rinaldi
    • Categories Constrained Nonlinear Optimization, Nonlinear Optimization, Nonsmooth Optimization Tags , , ,

    In this work, we consider multiobjective optimization problems with both bound constraints on the variables and general nonlinear constraints, where objective and constraint function values can only be obtained by querying a black box. We define a linesearch-based solution method, and we show that it converges to a set of Pareto stationary points. To this … Read more

    Derivative-free Methods for Mixed-Integer Constrained Optimization Problems

  • Giampaolo Liuzzi
  • Stefano Lucidi
  • Francesco Rinaldi
    • Categories (Mixed) Integer Nonlinear Programming, Applications - OR and Management Sciences, Constrained Nonlinear Optimization

    Methods which do not use any derivative information are becoming popular among researchers, since they allow to solve many real-world engineering problems. Such problems are frequently characterized by the presence of discrete variables which can further complicate the optimization process. In this paper, we propose derivative-free algorithms for solving continuously differentiable Mixed Integer NonLinear Programming … Read more

    Exploiting derivative-free local searches in DIRECT-type algorithms for global optimization

  • Giampaolo Liuzzi
  • Stefano Lucidi
  • Veronica Piccialli
    • Categories Biomedical Applications, Global Optimization

    In this paper we consider bound constrained global optimization problems where first-order derivatives of the objective function can be neither computed nor approximated explicitly. For the solution of such problems the DIRECT Algorithm has been proposed which has strong convergence properties and a good ability to locate promising regions of the feasible domain. However, the … Read more