Bilevel innovization
Julian Schulte, Niclas Feldkamp, Sören Bergmann, Volker Nissen · Proceedings of the Genetic and Evolutionary Computation Conference Companion · 2018
Determining a scheduling system's framework conditions (e.g. number of vehicles or employees) results in a hierarchical optimization problem, which can be solved through evolutionary bilevel optimization. In this paper, we propose an approach to gain better understanding of a scheduling system's behavior by applying visual analytics on the whole set of evaluated solutions during the bilevel optimization procedure. The results show that bilevel innovization can be used to support the decision making process in a strategic planning context by providing useful information regarding the scheduling system's behavior.