14 citations · 32 across the 12 of their papers we have counts for
13 papers
Nonconvex optimization methods for ground states in disordered continuous-spin models
Ramgopal Agrawal, Lorenzo Ciarpaglini, Pierluigi Mansueto +4
This work explores the global optimization problem of finding lowest-energy configurations in disordered continuous-spin models from statistical physics, with a particular focus on…
A heavy-ball type curve search method for smooth convexly constrained optimization
Federica Donnini, Pierluigi Mansueto
This paper addresses smooth convexly constrained optimization problems where the Euclidean projection onto the feasible set is computationally tractable. Although momentum techniqu…
A Nonmonotone Front Descent Method for Bound-Constrained Multi-Objective Optimization
Pierluigi Mansueto
We introduce a nonmonotone extension of the Front Descent framework for multiobjective optimization. The method uses novel nonmonotone line searches that allow temporary increases…
Efficient globalization of heavy-ball type methods for unconstrained optimization based on curve searches
Federica Donnini, Matteo Lapucci, Pierluigi Mansueto
In this work, we deal with unconstrained nonlinear optimization problems. Specifically, we are interested in methods carrying out updates possibly along directions not of descent,…
Projection-based curve pattern search for black-box optimization over smooth convex sets
Xiaoxi Jia, Matteo Lapucci, Pierluigi Mansueto
In this paper, we deal with the problem of optimizing a black-box smooth function over a full-dimensional smooth convex set. We study sets of feasible curves that allow to properly…
Optimization-Driven Design of Monolithic Soft-Rigid Grippers
Pierluigi Mansueto, Mihai Dragusanu, Anjum Saeed +3
Sim-to-real transfer remains a significant challenge in soft robotics due to the unpredictability introduced by common manufacturing processes such as 3D printing and molding. Thes…
Combining Gradient Information and Primitive Directions for High-Performance Mixed-Integer Optimization
Matteo Lapucci, Giampaolo Liuzzi, Stefano Lucidi +1
In this paper we consider bound-constrained mixed-integer optimization problems where the objective function is differentiable w.r.t.\ the continuous variables for every configurat…
Effective Front-Descent Algorithms with Convergence Guarantees
Matteo Lapucci, Pierluigi Mansueto, Davide Pucci
In this manuscript, we address continuous unconstrained multi-objective optimization problems and we discuss descent type methods for the reconstruction of the Pareto set. Specific…
Memetic Differential Evolution Methods for Semi-Supervised Clustering
Pierluigi Mansueto, Fabio Schoen
In this paper, we propose an extension for semi-supervised Minimum Sum-of-Squares Clustering (MSSC) problems of MDEClust, a memetic framework based on the Differential Evolution pa…
A Bi-Objective Optimization Based Acquisition Strategy for Batch Bayesian Global Optimization
Francesco Carciaghi, Simone Magistri, Pierluigi Mansueto +1
In this paper, we deal with batch Bayesian Optimization (Bayes-Opt) problems over a box and we propose a novel bi-objective optimization (BOO) acquisition strategy to sample points…
Cardinality-Constrained Multi-Objective Optimization: Novel Optimality Conditions and Algorithms
Matteo Lapucci, Pierluigi Mansueto
In this paper, we consider multi-objective optimization problems with a sparsity constraint on the vector of variables. For this class of problems, inspired by the homonymous neces…
Improved Front Steepest Descent for Multi-objective Optimization
Matteo Lapucci, Pierluigi Mansueto
In this paper, we deal with the Front Steepest Descent algorithm for multi-objective optimization. We point out that the algorithm from the literature is often incapable, by design…
A Memetic Procedure for Global Multi-Objective Optimization
Matteo Lapucci, Pierluigi Mansueto, Fabio Schoen
In this paper we consider multi-objective optimization problems over a box. The problem is very relevant and several computational approaches have been proposed in the literature.…