Operations Research, Combinatorial Optimization and Constraints - ROC
Leader: Marie-José HUGUET
The research domains considered by the ROC Team (Operations Research, Combinatorial Optimization and Constraints) are branches of Operations Research and/or Artificial Intelligence (more specifically Constraint Programming).
The team carries out researches on models and methods for solving efficiently combinatorial (or discrete) optimization problems and constraint satisfaction problems. To achieve this aim, the team develops on the one hand studies on the structure of fundamental problems in graph theory, scheduling, constraint satisfaction, and integer programming. On the other hand, the team aims at designing and evaluating generic solution search methodologies to cope with combinatorial explosion of the search space exploration while solving problems. The proposed models and methods concern at first hand combinatorial optimization problems (COP) in their deterministic and centralized form with a special emphasis on resource-constrained scheduling problems and vehicle routing problems. However, to increase the applicability of the developed approaches, the team seeks solutions to incorporate uncertainty through robustness considerations, multiple objectives/and or decision centers. Under the same objective, the team aims at confronting the proposed methods to the real world by considering industrial engineering and human aspects and/or applications to various domains including transportation, manufacturing and supply chain management, energy management, aeronautics and space. To favor the dissemination of its research and the confrontation of the developed methods to the international community, the team aims also to develop non-commercial solvers and participate to international competitions.