Quantitative Approaches to enable the Automated Planning of Adaptive Process Models

Nowadays, process models are valuable tools for a variety of activities in the business environment. They are used, for example, to train employees, to document processes or as part of company audits and to align the IT strategy with the company goals. However, process models are still created manually in many cases. This manual creation proves to be tedious, thus cost-intensive and especially error-prone. The dissertation at hand addresses this problem area and presents approaches for the automated planning of adaptive process models. Adaptive process models are those process models that take into account factors that require flexibility in processes. This includes, for example, the context of processes or the actors involved in the process