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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/20719

Title: Using process mining to model interarrival times: investigating the sensitivity of the ARPRA framework
Authors: Martin, Niels
Depaire, Benoit
Caris, An
Issue Date: 2015
Publisher: IEEE
Citation: Yilmaz, L.; Chan, W.K.V.; Moon, I.; Roeder, T.M.K.; Macal, C.; Rossetti, M.D. (Ed.). Proceedings of the 2015 Winter Simulation Conference, p. 868-879
Series/Report: Proceedings of the Winter Simulation Conference
Abstract: Accurately modeling the interarrival times (IAT) is important when constructing a business process simulation model given its influence on process performance metrics such as the average flow time. To this end, the use of real data from information systems is highly relevant as it becomes more readily available. This paper considers event logs, a particular type of file containing process execution information, as a data source. To retrieve an IAT input model from event logs, the recently developed ARPRA framework is used, which is the first algorithm that explicitly integrates the notion of queues. This paper investigates ARPRA's sensitivity to the initial parameter set estimate and the size of the original event log. Experimental results show that (i) ARPRA is fairly robust for the specification of the initial parameter estimate and (ii) ARPRA's output represents reality more closely for larger event logs than for smaller logs.
URI: http://hdl.handle.net/1942/20719
Link to publication: http://www.informs-sim.org/wsc15papers/075.pdf
DOI: 10.1109/WSC.2015.7408223
ISI #: 000399133900075
ISBN: 9781467397414
ISSN: 0891-7736
Category: C1
Type: Proceedings Paper
Validation: vabb, 2018
Appears in Collections: Research publications

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