Discrete optimisation for automatic decision-making in large-scale complex systems

PI: Elina Rönnberg (LiU); co-PI: Susanna F. de Rezende (LU)

Improved methods for solving discrete optimisation problems have a great potential to contribute to sustainability and energy efficiency, as well as to trustworthiness of systems. The goal of this project is to push the limits for which scheduling and resource allocation problems can be successfully solved. Both the mathematical programming and computer science communities have long and strong traditions of developing optimisation methods for such problems, but with limited interaction. The core novelty of this project is in hybridising methods from these communities and integrating them into decomposition frameworks.

Project number: D5