Efficient business processes play a major role in the success of companies. Business processes are captured and described by models that serve, for instance, as a starting point for implementing processes in a service-oriented way or for performance analysis. To support process modelers via methods and techniques (e.g., algorithms) in an automated manner, several research fields such as process mining and automated planning of process models have emerged. In particular, the aim of the latter research field is to enable the automated construction of process models using planning techniques. To this end, an automated construction of control flow patterns in process models is necessary. However, this task currently remains a widely unsolved issue for the central patterns parallel split and synchronization. We introduce novel concepts, which, in contrast to existing approaches, allow the construction of complex parallelizations (e.g., nested parallelizations and parallelizations with an arbitrary length of path segments) and are able to identify the set of feasible parallelizations. Moreover, we propose an algorithm facilitating the automated construction of parallel splits and synchronizations in process models. Our approach is evaluated according to key properties such as completeness, correctness and computational complexity. Furthermore, both the practical applicability within several real-world processes of different companies in various contexts as well as the practical utility of our approach are verified. The presented research expands the boundaries of automated planning of process models, adds more analytical rigor to automatic techniques in the context of business process management and contributes to control flow pattern theory.