Resumen:

Time Prediction on Multi-perspective Declarative Business Processes

Abstract. Process-aware information systems (PAISs) are increasingly used to provide flexible support for business processes. The support given through a PAIS is greatly enhanced when it is able to provide accurate time predictions which is typically a very challenging task. Predictions should be (1) multi-dimensional and (2) not based on a single process in- stance. Furthermore, the prediction system should be able to (3) adapt to changing circumstances, and (4) deal with multi-perspective declarative languages (e.g., models which consider time, resource, data and control flow perspectives). In this work, a novel approach for generating time predictions considering the aforementioned characteristics is proposed. For this, rst, a multi-perspective constraint-based language is used to model the scenario. Thereafter, an optimized enactment plan (represent- ing a potential execution alternative) is generated from such a model considering the current execution state of the process instances. Finally, predictions are performed by evaluating a desired function over this en- actment plan. To evaluate the applicability of our approach in practical settings we apply it to a real process scenario. Despite the high com- plexity of the considered problems, results indicate that our approach produces a satisfactory number of good predictions in a reasonable time. This research has been supported by the Spanish MINECO R&D Projects Pololas TIN2016-76956-C3-2-R and PLAN MINER TIN2015-71618-R.