2 citations · 2 across the 4 of their papers we have counts for
4 papers · 1 filter
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…
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…
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…
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…