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 | Source: | 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. | Document URI: | http://hdl.handle.net/1942/20719 | Link to publication/dataset: | http://www.informs-sim.org/wsc15papers/075.pdf | ISBN: | 9781467397414 | DOI: | 10.1109/WSC.2015.7408223 | ISI #: | 000399133900075 | Rights: | © 2015 IEEE | Category: | C1 | Type: | Proceedings Paper | Validations: | ecoom 2018 vabb 2018 |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
075.pdf Restricted Access | Published version | 239.94 kB | Adobe PDF | View/Open Request a copy |
SCOPUSTM
Citations
1
checked on Sep 2, 2020
WEB OF SCIENCETM
Citations
7
checked on Oct 12, 2024
Page view(s)
74
checked on Sep 7, 2022
Download(s)
10
checked on Sep 7, 2022
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.