152 citations · 308 across the 30 of their papers we have counts for
4 papers · 1 filter
A learning-based algorithm to quickly compute good primal solutions for Stochastic Integer Programs
Yoshua Bengio, Emma Frejinger, Andrea Lodi +2
We propose a novel approach using supervised learning to obtain near-optimal primal solutions for two-stage stochastic integer programming (2SIP) problems with constraints in the f…
A language processing algorithm for predicting tactical solutions to an operational planning problem under uncertainty
Emma Frejinger, Eric Larsen
This paper is devoted to the prediction of solutions to a stochastic discrete optimization problem. Through an application, we illustrate how we can use a state-of-the-art neural m…
A tutorial on recursive models for analyzing and predicting path choice behavior
Maëlle Zimmermann, Emma Frejinger
The problem at the heart of this tutorial consists in modeling the path choice behavior of network users. This problem has been extensively studied in transportation science, where…
Predicting Tactical Solutions to Operational Planning Problems under Imperfect Information
Eric Larsen, Sébastien Lachapelle, Yoshua Bengio +3
This paper offers a methodological contribution at the intersection of machine learning and operations research. Namely, we propose a methodology to quickly predict tactical soluti…