BONUS

Being ubiquitous to countless modern engineering and scientic applications, big optimization requires models increasingly large-scale to deal with a growing amount of decision variables and conflicting expensive objectives. The goal of Bonus is to come up with cutting-edge approaches at the interface of three research lines that constitute the scientic program of the project and the subject of current and forthcoming collaborations: decomposition-based optimization, Machine Learning-assisted optimization and ultra-scale optimization. From application and industrial transfer point of view, we target sustainability-aware complex scheduling and engineering design applications.