Research

My objective is to develop methodological contributions, particularly theorems, that result in algorithms which are not only theoretically sound but also practically effective. These algorithms are designed to address significant issues that extend beyond the realm of mathematics, with a primary focus on enhancing decision-making within industrial operations. This ambition has guided me to a career in Operations Research, where I explore a research path that intersects Combinatorial Optimization with Machine Learning.

I have a strong taste for applying these concepts to industry, especially within the transportation and supply chain sectors. This passion has driven me to initiate and oversee numerous industrial collaborations, including two notable partnerships.

• Artificial Intelligence for Air Transport chair between Air France and École des Ponts.
• Operations Research and Machine Learning for supply chain with Renault Supply Chain.

I try to balance my research between fundamental aspects, which aim at developing new methodologies, and more practical ones that make the work when optimizing industrial partners processes. Over the years, this balance has been very fruitful. There is nothing better than a challenging industrial application to identify deep scientific questions. Addressing such challenges requires developing new generations of algorithms, which can in turn be applied on a diversity of industrial applications.

If you want to know more about Operations Research, why it is important, what I believe are the main challenges of the field, and why I chose this research agenda, please read this blog post.

My methodological research aims at addressing what I believe is the the main challenge for Operations Research : developing scalable and data driven optimization algorithms that make industrial processes more efficient and resilient. The main line I follow consists in developing algorithms using combinatorial optimization and machine learning tools simultaneously. Besides, combinatorial optimization remains the workhorse of operations research. Hence, a significant part of my research is focused on developing algorithms for emerging combinatorial optimization problems, notably in the context of the ecological transition.

My main fields of applications are derived from long term partnerships with Air France and Renault. In Transportation, I work on operational aspects, notably in terms of vehicle routing and crew pairing, on revenue management, and on predictive maintenance and its impact on operations. Integrated problems that deal with revenue management and operational aspects simultaneously are my favorite. In Supply Chain, I am notably interested in inbound, outbound, and reverse logistic, as well as assembly line and warehouse management problems. Again, integrated approach that take an end-to-end perspective on demand and supply are my favorite. Beyond these two fields, I get easily interested in any challenging industrial process optimization problem.