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Sitemap
A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
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Posts
Future Blog Post
Published:
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Blog Post number 4
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 2
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 1
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
publications
Learning with Combinatorial Optimization Layers: a Probabilistic Approach
Published in preprint, 2022
This paper introduces a Julia library of Machine Learning for Operations Research, as well as a new probabilistic approach.
Recommended citation: Guillaume Dalle, Léo Baty, Louis Bouvier, Axel Parmentier, "Learning with Combinatorial Optimization Layers: a Probabilistic Approach" https://arxiv.org/pdf/2207.13513.pdf
Solving a Continent-Scale Inventory Routing Problem at Renault
Published in Transportation Science, 2023
This paper is the fruit of a partnership with Renault.
Recommended citation: Louis Bouvier, Guillaume Dalle, Axel Parmentier, Thibaut Vidal, "Solving a Continent-Scale Inventory Routing Problem at Renault" https://pubsonline.informs.org/doi/10.1287/trsc.2022.0342
Combinatorial Optimization and Machine Learning for Dynamic Inventory Routing
Published in preprint, 2024
This preprint is about structured learning for combinatorial multistage stochastic optimization.
Recommended citation: Toni Greif, Louis Bouvier, Christoph M. Flath, Axel Parmentier, Sonja U. K. Rohmer, Thibaut Vidal, "Combinatorial Optimization and Machine Learning for Dynamic Inventory Routing" https://arxiv.org/abs/2402.04463
talks
Large Neighborhood Search and Structured Prediction for the Inventory Routing Problem
Published:
We consider a large-scale multi-depot multi-commodity Inventory Routing Problem (IRP) to model the packaging return logistics of a major European car manufacturer. No algorithm is known to properly scale to our context. We propose a Large Neighborhood Search (LNS) based on common routing neighborhoods and two new ones: the reinsertion of a customer and a commodity in the IRP solution. We also try to bypass the heavy computations of the LNS leveraging recent ideas in Machine Learning for Operations Research in structured prediction.
teaching
Teaching assistant
Undergraduate course, Ecole des Ponts ParisTech, 2021
Teaching assistant in optimization for first-year engineering students.
Teaching assistant
Post-graduate course, Ecole des Ponts ParisTech, 2022
Teaching assistant (course + exercises + hackathon) in operations research for second-year engineering students.
Teaching assistant
Post-graduate course, Ecole des Ponts ParisTech, 2023
Teaching assistant (course + exercises + hackathon) in operations research for second-year engineering students.