Geodesic
An approach to business process simulation using mined probabilistic models
Computer Science and Information Systems, Tome 15 (2018) no. 1.

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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.
Keywords: Probabilistic business process model, Business process simulation, Simulation model generation, Process mining 
@article{CSIS_2018_15_1_a2,
     author = {Titas Savickas and Olegas Vasilecas},
     title = {An approach to business process simulation using mined probabilistic models},
     journal = {Computer Science and Information Systems},
     publisher = {mathdoc},
     volume = {15},
     number = {1},
     year = {2018},
     url = {http://geodesic.mathdoc.fr/item/CSIS_2018_15_1_a2/}
}
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Titas Savickas; Olegas Vasilecas. An approach to business process simulation using mined probabilistic models. Computer Science and Information Systems, Tome 15 (2018) no. 1. http://geodesic.mathdoc.fr/item/CSIS_2018_15_1_a2/