Business Process Simulation represents a powerful instrument for business analysts when analyzing and comparing business processes. Most of the state-of-the-art business process simulators, however, rely on Discrete event simulation, which requires various unrealistic assumptions and simplifications to perform experiments. Predictive Process Monitoring, on the other hand, offers a viable way to complete ongoing traces or to generate entire traces from scratch, via predictions of the next activities and their attributes. Predictive models, though, are usually based on black-box approaches that make it difficult to reason on what-if scenarios. RIMS_Tool is a hybrid business process simulator that aims at combining predictive models built from data and Discrete event simulation at runtime in a white-box manner. The proposed tool, thus, is able to exploit the strengths and avoid the limitations of both approaches.
ICPM Doctoral Consortium and Demo Track 2023 / Meneghello, Francesca; Di Francescomarino, Chiara; Ghidini, Chiara. - (2024). (Intervento presentato al convegno Doctoral Consortium and Demo Track 2023 at the International Conference on Process Mining 2023 co-located with the 5th International Conference on Process Mining (ICPM 2023) tenutosi a Rome, Italy).
ICPM Doctoral Consortium and Demo Track 2023
Francesca Meneghello
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2024
Abstract
Business Process Simulation represents a powerful instrument for business analysts when analyzing and comparing business processes. Most of the state-of-the-art business process simulators, however, rely on Discrete event simulation, which requires various unrealistic assumptions and simplifications to perform experiments. Predictive Process Monitoring, on the other hand, offers a viable way to complete ongoing traces or to generate entire traces from scratch, via predictions of the next activities and their attributes. Predictive models, though, are usually based on black-box approaches that make it difficult to reason on what-if scenarios. RIMS_Tool is a hybrid business process simulator that aims at combining predictive models built from data and Discrete event simulation at runtime in a white-box manner. The proposed tool, thus, is able to exploit the strengths and avoid the limitations of both approaches.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.