Search Results for author: Emma Frejinger

Found 13 papers, 2 papers with code

A Survey of Contextual Optimization Methods for Decision Making under Uncertainty

no code implementations17 Jun 2023 Utsav Sadana, Abhilash Chenreddy, Erick Delage, Alexandre Forel, Emma Frejinger, Thibaut Vidal

Recently there has been a surge of interest in operations research (OR) and the machine learning (ML) community in combining prediction algorithms and optimization techniques to solve decision-making problems in the face of uncertainty.

Decision Making Decision Making Under Uncertainty

Scope Restriction for Scalable Real-Time Railway Rescheduling: An Exploratory Study

1 code implementation5 May 2023 Erik Nygren, Christian Eichenberger, Emma Frejinger

Instead, we propose defining a core problem that restricts a rescheduling problem in response to a disturbance to only trains that need to be rescheduled, hence restricting the scope in both time and space.

Arc travel time and path choice model estimation subsumed

no code implementations25 Oct 2022 Sobhan Mohammadpour, Emma Frejinger

We propose a method for maximum likelihood estimation of path choice model parameters and arc travel time using data of different levels of granularity.

Fast Continuous and Integer L-shaped Heuristics Through Supervised Learning

no code implementations2 May 2022 Eric Larsen, Emma Frejinger, Bernard Gendron, Andrea Lodi

Our extensive empirical analysis is grounded in standardized families of problems derived from stochastic server location (SSLP) and stochastic multi knapsack (SMKP) problems available in the literature.


Minimizing Entropy to Discover Good Solutions to Recurrent Mixed Integer Programs

no code implementations7 Feb 2022 Charly Robinson La Rocca, Emma Frejinger, Jean-François Cordeau

Current state-of-the-art solvers for mixed-integer programming (MIP) problems are designed to perform well on a wide range of problems.

Periodic Freight Demand Estimation for Large-scale Tactical Planning

no code implementations19 May 2021 Greta Laage, Emma Frejinger, Gilles Savard

In practice, demand is predicted by a time series forecasting model and the periodic demand is the average of those forecasts.

Decision Making Time Series +1

Reinforcement Learning for Freight Booking Control Problems

no code implementations29 Jan 2021 Justin Dumouchelle, Emma Frejinger, Andrea Lodi

Routinely solving such operational problems when deploying reinforcement learning algorithms may be too time consuming.

BIG-bench Machine Learning Decision Making +3

Assessing the Impact: Does an Improvement to a Revenue Management System Lead to an Improved Revenue?

no code implementations13 Jan 2021 Greta Laage, Emma Frejinger, Andrea Lodi, Guillaume Rabusseau

This is a challenging problem as it corresponds to the difference between the generated value and the value that would have been generated keeping the system as before.

counterfactual Management

A learning-based algorithm to quickly compute good primal solutions for Stochastic Integer Programs

1 code implementation17 Dec 2019 Yoshua Bengio, Emma Frejinger, Andrea Lodi, Rahul Patel, Sriram Sankaranarayanan

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 first and second stages.

A tutorial on recursive models for analyzing and predicting path choice behavior

no code implementations2 May 2019 Maëlle Zimmermann, Emma Frejinger

The problem at the heart of this tutorial consists in modeling the path choice behavior of network users.

Predicting Tactical Solutions to Operational Planning Problems under Imperfect Information

no code implementations22 Jan 2019 Eric Larsen, Sébastien Lachapelle, Yoshua Bengio, Emma Frejinger, Simon Lacoste-Julien, Andrea Lodi

We formulate the problem as a two-stage optimal prediction stochastic program whose solution we predict with a supervised machine learning algorithm.

BIG-bench Machine Learning Management

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