2 citations · 2 across the 5 of their papers we have counts for
6 papers · 1 filter
First-Order Methods for Wasserstein Distributionally Robust Constrained Optimization
Hubert Villuendas, Mathieu Besançon, Jérôme Malick
We consider constrained problems in which input data are affected by errors. In such settings, Wasserstein distributionally robust optimization provides a principled framework to m…
A Frank-Wolfe-based primal heuristic for quadratic mixed-integer optimization
Gioni Mexi, Deborah Hendrych, Sébastien Designolle +2
We propose a primal heuristic for quadratic mixed-integer problems. Our method extends the Boscia framework -- originally a mixed-integer convex solver leveraging a Frank-Wolfe-bas…
Knapsack with compactness: a semidefinite approach
Hubert Villuendas, Mathieu Besançon, Jérôme Malick
The min-knapsack problem with compactness constraints extends the classical knapsack problem, in the case of ordered items, by introducing a restriction ensuring that they cannot b…
A Frank-Wolfe Algorithm for Oracle-based Robust Optimization
Mathieu Besançon, Jannis Kurtz
We tackle robust optimization problems under objective uncertainty in the oracle model, i.e., when the deterministic problem is solved by an oracle. The oracle-based setup is favor…
Network Design for the Traffic Assignment Problem with Mixed-Integer Frank-Wolfe
Kartikey Sharma, Deborah Hendrych, Mathieu Besançon +1
We tackle the network design problem for centralized traffic assignment, which can be cast as a mixed-integer convex optimization (MICO) problem. For this task, we propose differen…
A Bilevel Approach to Optimal Price-Setting of Time-and-Level-of-Use Tariffs
Mathieu Besançon, Miguel F. Anjos, Luce Brotcorne +1
Time-and-Level-of-Use (TLOU) is a recently proposed pricing policy for energy, extending Time-of-Use with the addition of a capacity that users can book for a given time frame, red…