CD Laboratory for Artificial Intelligence and Optimization for Planning and Scheduling

This CD Laboratory researches innovative solution techniques for resource planning and scheduling problems based on artificial intelligence and optimisation.

Problems in resource planning and scheduling occur in a variety of areas, such as healthcare, industrial production, educational institutions and public transport. Typical problems are project planning and resource allocation for machines and assembly systems, schedules in sports and logistics, scheduling in the healthcare system and the creation of employee rosters. Practical problems in these areas pose a major challenge and their solutions have an impact on the people involved, the efficiency of work processes and the costs for host institutions. Due to the high demand for automation in industrial applications (e.g. Industry 4.0), research in this field is currently very important. In addition, the new fields of work involve challenging problems that have not yet been optimally solved due to the enormous size of the search space for potential solutions.

The aim of this project is to develop innovative problem-solving techniques based on the synergy of artificial intelligence and optimisation. These methods utilise machine learning for the automatic selection, configuration and design of algorithms. Furthermore, new strategies based on the hybridisation of methods from both areas are proposed.

The new techniques are used to solve very large resource planning and scheduling problems, including in personnel planning, production planning and the allocation of tests in industrial laboratories. The solutions developed should also contribute to solving other NP-hard problems relevant to complexity theory.