1 citations · 1 across the 5 of their papers we have counts for
6 papers
Intermediate Bilevel Optimization: Modeling Endogenous Follower Tie-Breaking Behavior
Maria Bazotte, Margarida Carvalho, Thibaut Vidal
In bilevel optimization, optimistic and pessimistic follower behaviors are the most commonly used forms to define how the follower ties-breaks among multiple optimal solutions. In…
Optimization by Directional Attacks: Solving Problems with Neural Network Surrogates
Pierre-Yves Bouchet, Thibaut Vidal
This paper tackles optimization problems whose objective and constraints involve a trained Neural Network (NN), where the goal is to maximize subject to ,…
Two-Stage Stochastic Capacity Expansion in Stable Matching under Truthful or Strategic Preference Uncertainty
Maria Bazotte, Margarida Carvalho, Thibaut Vidal
Recent studies on many-to-one matching markets have explored agents with flexible capacity and truthful preference reporting, focusing on mechanisms that jointly design capacities…
Dual Policy Reinforcement Learning for Real-time Rebalancing in Bike-sharing Systems
Jiaqi Liang, Defeng Liu, Sanjay Dominik Jena +2
Bike-sharing systems play a crucial role in easing traffic congestion and promoting healthier lifestyles. However, ensuring their reliability and user acceptance requires effective…
Contextual Stochastic Vehicle Routing with Time Windows
Breno Serrano, Alexandre M. Florio, Stefan Minner +2
We study the vehicle routing problem with time windows (VRPTW) and stochastic travel times, in which the decision-maker observes related contextual information, represented as feat…
Solving Two-Stage Stochastic Programs with Endogenous Uncertainty via Random Variable Transformation
Maria Bazotte, Margarida Carvalho, Thibaut Vidal
Real-world decision-making problems often involve decision-dependent uncertainty, where the probability distribution of the random vector depends on the model decisions. Few studie…