Strategies to automatically derive a process model from a configurable process model based on event data

M. Arriagada-Benítez (Corresponding author), M. Sepúlveda, J. Munoz-Gama, J.C.A.M. Buijs

Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

7 Citaties (Scopus)

Uittreksel

Configurable process models are frequently used to represent business workflows and other discrete event systems among different branches of large organizations: they unify commonalities shared by all branches and describe their differences, at the same time. The configuration of such models is usually done manually, which is challenging. On the one hand, when the number of configurable nodes in the configurable process model grows, the size of the search space increases exponentially. On the other hand, the person performing the configuration may lack the holistic perspective to make the right choice for all configurable nodes at the same time, since choices influence each other. Nowadays, information systems that support the execution of business processes create event data reflecting how processes are performed. In this article, we propose three strategies (based on exhaustive search, genetic algorithms and a greedy heuristic) that use event data to automatically derive a process model from a configurable process model that better represents the characteristics of the process in a specific branch. These strategies have been implemented in our proposed framework and tested in both business-like event logs as recorded in a higher educational enterprise resource planning system and a real case scenario involving a set of Dutch municipalities.

TaalEngels
Artikelnummer1023
Aantal pagina's28
TijdschriftApplied Sciences
Volume7
Nummer van het tijdschrift10
DOI's
StatusGepubliceerd - 4 okt 2017

Vingerafdruk

commonality
Industry
information systems
Enterprise resource planning
Discrete event simulation
configurations
genetic algorithms
planning
resources
Information systems
Genetic algorithms

Trefwoorden

    Citeer dit

    Arriagada-Benítez, M., Sepúlveda, M., Munoz-Gama, J., & Buijs, J. C. A. M. (2017). Strategies to automatically derive a process model from a configurable process model based on event data. Applied Sciences, 7(10), [1023]. DOI: 10.3390/app7101023
    Arriagada-Benítez, M. ; Sepúlveda, M. ; Munoz-Gama, J. ; Buijs, J.C.A.M./ Strategies to automatically derive a process model from a configurable process model based on event data. In: Applied Sciences. 2017 ; Vol. 7, Nr. 10.
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    title = "Strategies to automatically derive a process model from a configurable process model based on event data",
    abstract = "Configurable process models are frequently used to represent business workflows and other discrete event systems among different branches of large organizations: they unify commonalities shared by all branches and describe their differences, at the same time. The configuration of such models is usually done manually, which is challenging. On the one hand, when the number of configurable nodes in the configurable process model grows, the size of the search space increases exponentially. On the other hand, the person performing the configuration may lack the holistic perspective to make the right choice for all configurable nodes at the same time, since choices influence each other. Nowadays, information systems that support the execution of business processes create event data reflecting how processes are performed. In this article, we propose three strategies (based on exhaustive search, genetic algorithms and a greedy heuristic) that use event data to automatically derive a process model from a configurable process model that better represents the characteristics of the process in a specific branch. These strategies have been implemented in our proposed framework and tested in both business-like event logs as recorded in a higher educational enterprise resource planning system and a real case scenario involving a set of Dutch municipalities.",
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    Arriagada-Benítez, M, Sepúlveda, M, Munoz-Gama, J & Buijs, JCAM 2017, 'Strategies to automatically derive a process model from a configurable process model based on event data' Applied Sciences, vol. 7, nr. 10, 1023. DOI: 10.3390/app7101023

    Strategies to automatically derive a process model from a configurable process model based on event data. / Arriagada-Benítez, M. (Corresponding author); Sepúlveda, M.; Munoz-Gama, J.; Buijs, J.C.A.M.

    In: Applied Sciences, Vol. 7, Nr. 10, 1023, 04.10.2017.

    Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

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    Arriagada-Benítez M, Sepúlveda M, Munoz-Gama J, Buijs JCAM. Strategies to automatically derive a process model from a configurable process model based on event data. Applied Sciences. 2017 okt 4;7(10). 1023. Beschikbaar vanaf, DOI: 10.3390/app7101023