An approach to business process simulation using mined probabilistic models

Titas Savickas1 and Olegas Vasilecas1

  1. Information Systems Research Labouratory, Vilnius Gediminas Technical University
    10223 Vilnius, Lithuania


Business process analysis and improvement leads to more competitive enterprises. There are many approaches on how analyze business processes but simulation is still not widely employed due to high costs associated with simulation model creation. In this paper, an approach on how to automatically generate dynamic business process simulation model is presented. The approach discovers belief network of the process from an event log and uses it to automatically generate a simulation model. Such model then can be further customized to facilitate analysis. For evaluation of the approach, three event logs were taken and simulation models were dis-covered and simulated to generate simulation result event log which then were compared to the source event logs again by applying conformance checking methods. The evaluation showed that the approach, in general, could be used for initial simulation model generation.

Key words

Probabilistic business process model, Business process simulation, Simulation model generation, Process mining

Digital Object Identifier (DOI)

Publication information

Volume 15, Issue 1 (January 2018)
Year of Publication: 2018
ISSN: 1820-0214 (Print) 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Savickas, T., Vasilecas, O.: An approach to business process simulation using mined probabilistic models. Computer Science and Information Systems, Vol. 15, No. 1, 31–50. (2018),