activity
20192026
most citedConvex mixed-integer optimization with Frank-Wolfe methods

2 citations · 3 across the 7 of their papers we have counts for

collaborators

9 papers

math.OC2026

Discrete eigenvalue optimization from entropic smoothing and first-order methods

Deborah Hendrych, Mathieu Besançon, Sebastian Pokutta

We study the maximization of the minimum eigenvalue under combinatorial and integrality constraints. We propose a new approach based on branch-and-bound combines entropic smoothing…

math.OC2025

Boscia.jl: A review and tutorial

Wenjie Xiao, Deborah Hendrych, Mathieu Besançon +1

Mixed-integer nonlinear optimization (MINLP) comprises a large class of problems that are challenging to solve and exhibit a wide range of structures. The Boscia framework (Hendryc…

math.OC2025

Efficient Quadratic Corrections for Frank-Wolfe Algorithms

Jannis Halbey, Seta Rakotomandimby, Mathieu Besançon +2

We develop a Frank-Wolfe algorithm with corrective steps, generalizing previous algorithms including blended conditional gradients, blended pairwise conditional gradients, and full…

math.OC2025

Mixed-Integer Optimization for Loopless Flux Distributions in Metabolic Networks

Hannah Troppens, Mathieu Besançon, St. Elmo Wilken +1

Constraint-based metabolic models can be used to investigate the intracellular physiology of microorganisms. These models couple genes to reactions, and typically seek to predict m…

math.OC2025

Secant Line Search for Frank-Wolfe Algorithms

Deborah Hendrych, Mathieu Besançon, David Martínez-Rubio +1

We present a new step-size strategy based on the secant method for Frank-Wolfe algorithms. This strategy, which requires mild assumptions about the function under consideration, ca…

math.OC2024

The Pivoting Framework: Frank-Wolfe Algorithms with Active Set Size Control

Elias Wirth, Mathieu Besançon, Sebastian Pokutta

We propose the pivoting meta algorithm (PM) to enhance optimization algorithms that generate iterates as convex combinations of vertices of a feasible region $C\subseteq \mathbb{R}…

math.OC2024

Optimisation models for the design of multiple self-consumption loops in semi-rural areas

Yohann Chasseray, Mathieu Besançon, Xavier Lorca +1

Collective electricity self-consumption gains increasing interest in a context where localised consumption of energy is a lever of sustainable development. While easing energy dist…

math.OC2022★ 2 cited

Convex mixed-integer optimization with Frank-Wolfe methods

Deborah Hendrych, Hannah Troppens, Mathieu Besançon +1

Mixed-integer nonlinear optimization encompasses a broad class of problems that present both theoretical and computational challenges. We propose a new type of method to solve thes…

math.OC2019★ 1 cited

Robust Bilevel Optimization for Near-Optimal Lower-Level Solutions

Mathieu Besançon, Miguel F. Anjos, Luce Brotcorne

Bilevel optimization problems embed the optimality of a subproblem as a constraint of another optimization problem. We introduce the concept of near-optimality robustness for bilev…