Our research in this area, coordinated by Professor Rei, focuses on the development and application of models and methods to entire classes of problems and their applications.

Theme 1.1 – Modeling and Solution Methods for Complex Planning Problems [Anaya-Arenas, Cherkesly, Crainic, Djeumou, Gruson, Jena, Ortmann, Rei, Zbib]: This theme focuses on modeling systems and decision-making problems using mathematical programming, as well as solving them (i.e., identifying optimal plans).

Theme 1.2 – Representation and Treatment of Uncertainty to Increase System Resilience [Anaya-Arenas, Crainic, Jena, Ortmann, Quesnel, Rei, Zbib]: This theme aims to characterize and reduce uncertainty, and includes the integration of machine learning into decision-making under uncertainty (stochastic and robust optimization).

Theme 1.3 – Empirical Research [Bendavid, Jena, Lachapelle, Ortmann, Paulhiac, Quesnel]: Creating procedures for data capture (IoT), collection, and processing (quantitative and qualitative) is at the core of this theme. This covers data obtained through interviews, surveys, and publicly available sources.

Theme 1.4 – Large-Scale Data Processing [Bendavid, Jena, Maïzi, Ortmann, Rei]: The massive volume of available data creates a challenge for its utilization in management systems. This theme aims to advance knowledge on the integration of learning methods (e.g., data mining techniques) into planning models, the collection of large amounts of data (often in real-time) from diverse sources, and rapid data processing. The goal is to facilitate the use of information flows to monitor operations and system performance, enabling accurate forecasting and the adjustment of plans in response to changes.

Theme 1.5 – “Living Lab” Research Methods [Bendavid, Gruson, Maïzi]: This research emerges in a collaborative setting where users participate in innovation by cooperating with other stakeholders (technology solution providers, service providers, researchers, clients, etc.). This takes place within a neutral and controlled research environment to understand synergies, as well as to design and develop complex systems.

Professor Bendavid leads this axis, which focuses on developing tools for experimentation, validation, partner training, knowledge transfer, and implementation within real-world processes.

Theme 2.1 – Numerical Simulation [Anaya-Arenas, Bendavid, Jena, Maïzi, Ortmann]: This theme aims to create digital tools for the representation and simulation of complex systems. This is essential for validating the models developed in Axis 1, demonstrating results, facilitating technology transfer, and training our partners on these methods.

Theme 2.2 – Prototypes and Pilots [Bendavid, Maïzi, Paulhiac]: Developed by researchers, students, and industry professionals, these prototypes and pilots are designed to transition research outcomes to users and partners. This stage requires an interdisciplinary approach that takes into account the applied, technological, political, and social dimensions.

View our projects by theme

A. Intelligent Transport Systems

B. Health Services

C. Humanitarian Aid

D. Supply Chain Management

E. Digital Revolution for Businesses

F. Smart Cities