activity
20162024
most citedLearning to Configure Mathematical Programming Solvers by Mathematical Programming

5 citations · 16 across the 10 of their papers we have counts for

collaborators

11 papers

cs.AI2024★ 1 cited

The Algorithm Configuration Problem

Gabriele Iommazzo, Claudia D'Ambrosio, Antonio Frangioni +1

The field of algorithmic optimization has significantly advanced with the development of methods for the automatic configuration of algorithmic parameters. This article delves into…

math.OC2024★ 5 cited

Learning to Configure Mathematical Programming Solvers by Mathematical Programming

Gabriele Iommazzo, Claudia D'Ambrosio, Antonio Frangioni +1

We discuss the issue of finding a good mathematical programming solver configuration for a particular instance of a given problem, and we propose a two-phase approach to solve it.…

math.OC2024★ 4 cited

A learning-based mathematical programming formulation for the automatic configuration of optimization solvers

Gabriele Iommazzo, Claudia D'Ambrosio, Antonio Frangioni +1

We propose a methodology, based on machine learning and optimization, for selecting a solver configuration for a given instance. First, we employ a set of solved instances and conf…

math.OC2023★ 3 cited

Optimal Battery Charge Scheduling For Revenue Stacking Under Operational Constraints Via Energy Arbitrage

Alban Puech, Gorazd Dimitrov, Claudia D'Ambrosio

As the share of variable renewable energy sources increases in the electricity mix, new solutions are needed to build a flexible and reliable grid. Energy arbitrage with battery st…

math.OC2022★ 1 cited

Cutting planes for signomial programming

Liding Xu, Claudia D'Ambrosio, Leo Liberti +1

Cutting planes are of crucial importance when solving nonconvex nonlinear programs to global optimality, for example using the spatial branch-and-bound algorithms. In this paper, w…

math.OC2022

Comparing perspective reformulations for piecewise-convex optimization

Renan Spencer Trindade, Claudia D'Ambrosio, Antonio Frangioni +1

Our study is motivated by the solution of Mixed-Integer Non-Linear Programming (MINLP) problems with separable non-convex functions via the Sequential Convex MINLP technique, an it…

math.OC2022

Branch and Price for Submodular Bin Packing

Liding Xu, Claudia D'Ambrosio, Sonia Haddad Vanier +1

The Submodular Bin Packing (SMBP) problem asks for packing unsplittable items into a minimal number of bins for which the capacity utilization function is submodular. SMBP is equiv…

math.OC2020

Learning Discontinuous Piecewise Affine Fitting Functions using Mixed Integer Programming for Segmentation and Denoising

Ruobing Shen, Bo Tang, Leo Liberti +2

Piecewise affine functions are widely used to approximate nonlinear and discontinuous functions. However, most, if not all existing models only deal with fitting continuous functio…

math.OC2018

Strong Convex Nonlinear Relaxations of the Pooling Problem

James Luedtke, Claudia D'Ambrosio, Jeff Linderoth +1

We investigate new convex relaxations for the pooling problem, a classic nonconvex production planning problem in which input materials are mixed in intermediate pools, with the ou…

math.OC2017★ 2 cited

Random projections for trust region subproblems

Ky Vu, Pierre-Louis Poirion, Claudia D'Ambrosio +1

The trust region method is an algorithm traditionally used in the field of derivative free optimization. The method works by iteratively constructing surrogate models (often linear…

cs.CG2016

New error measures and methods for realizing protein graphs from distance data

Claudia D'Ambrosio, Ky Vu, Carlile Lavor +2

The interval Distance Geometry Problem (iDGP) consists in finding a realization in of a simple undirected graph with nonnegative intervals assigned to the…