CATIE (Centre Aquitain des Technologies de l’Information et Électroniques) is a non-profit organization created in 2014 based in the Région Nouvelle-Aquitaine. As a technology resources center specialized in digital technology, its main mission is to support SMEs and intermediate size companies in their digital transformation and to help them embracing and integrating related technologies.

Our collaboration with CATIE is about machine learning and optimization. We focus on problems related to shortest path problem with side constraints.

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Saint-Gobain Research Paris is an industrial research and development centre working for light and sustainable construction of the Saint-Gobain Group, the world leader in light and sustainable construction.

The collaboration is centered around the PhD thesis of Pierre Pinet.

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Past collaborations

Orange is a French multinational telecommunications corporation. The company specialises in mobile, landline, internet and Internet Protocol television (IPTV) services since 2006.

In 2023, a contract was signed with Orange for a PhD on network optimization. The PhD student is John Jairo Quiroga Orozco under the supervision of Boris Detienne and Pierre Pesneau.

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Renault is a French multinational automobile manufacturer established in 1899. The company produces a range of cars and vans and in the past, has manufactured trucks, tractors, tanks, buses/coaches, aircraft and aircraft engines, and autorail vehicles.

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EDF is the major French multinational electric utility company owned by the French state.

Optimizing nuclear unit outages is of significant economic importance for the French electricity company EDF, as these outages induce a substitute production by other more expensive means to fulfill electricity demand. This problem is quite challenging given the specific operating constraints of nuclear units, the stochasticity of both the demand and non-nuclear units availability, and the scale of the instances. To tackle these difficulties we used a combined decomposition approach. The operating constraints of the nuclear units were built into a Dantzig-Wolfe pricing subproblem whose solutions define the columns of a demand covering formulation. The scenarios of demand and non-nuclear units availability are handled in a Benders decomposition. Our approach is shown to scale up to the real-life instances of the French nuclear fleet.

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RTE is France’s Transmission System Operator. It is in charge of the high and ultra-high voltage electricity transmission network in France and of the electricity exchanges with the neighbouring countries. Its main role is to guarantee in real time the balance between electricity production and consumption.

In 2019, a contract was signed with RTE for a PhD on algorithms to speedup Benders’ decomposition. The PhD student was Xavier Blanchot under the supervision of François Clautiaux and Aurélien Froger.

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SNCF is the French Railway operator. This project was funded by TER Nouvelle Aquitaine.

This collaboration funded the PhD thesis of Mohamed Benkirane. The subject of the thesis was an integrated optimization approach for timetable and rolling stock rotations planning in the context of passenger railway traffic. Our approach was based on a time-space hyper-graph model, which can handle trains composed by multiple self-powered railcars on part of their paths.

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