My research interests focus on mathematical programming, namely the optimization of functions with or without constraint, particularly in a continuous nonlinear framework. In view of the uncertainty prevalent in the real world, I am particularly interested in the field of stochastic programming, combining probability theory and optimization. This field of mathematical optimization can provide solutions that apprehend the unknown factors, present or future, more adequately. This research encounters many applications, and I work in particular on model estimation issues, including discrete choice theory. Discrete choice models attempt to explain the decision factors leading individuals to make particular choices among finite sets of alternatives (purchase decisions, route choice, transportation mode, etc.). Finally, I am also interested in general issues of computer simulation, and transportation problems.

My main research area is the application of operations research to transportation and telecommunication planning. A large portion of my work deals with the development of efficient metaheuristics for solving difficult problems in this area. As co-director of the Laboratory on Intelligent Transportation Systems of the Centre for Research on Transportation, I am also very interested in all real-time transportation planning problems.

My research interests focus on the development of metaheuristics, such as tabu search and genetic algorithms, for solving discrete optimization problems in the transportation domain. I am particularly interested in vehicle routing problems with different side constraints, like service time windows at customer locations. These problems can model many real-world applications such as distribution of goods by commercial vehicles, courier services, para-transit services, etc. I also study dynamic variants of these problems when customer requests dynamically occur over time and must be integrated in real-time into the current routes.