ILP-Based Process Discovery Using Hybrid Regions

The language-based theory of regions, stemming from the area of Petri net synthesis, forms a fundamental basis for Integer Linear Programming (ILP)-based process discovery. Based on example behavior in an event log, a process model is derived that aims to describe the observed behavior. Building on top of the existing ILP-formulation, we present a new ILP-based process discovery formulation that unifies two existing types of language-based regions and, additionally, we present a generalized ILP objective function that captures both region-types and helps us to find suitable process discovery results.