Version 1
: Received: 31 August 2017 / Approved: 1 September 2017 / Online: 1 September 2017 (17:14:50 CEST)
How to cite:
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. Preprints2017, 2017090003. https://doi.org/10.20944/preprints201709.0003.v1
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. Preprints 2017, 2017090003. https://doi.org/10.20944/preprints201709.0003.v1
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. Preprints2017, 2017090003. https://doi.org/10.20944/preprints201709.0003.v1
APA Style
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. Preprints. https://doi.org/10.20944/preprints201709.0003.v1
Chicago/Turabian Style
Arriagada-Benítez, M., Jorge Munoz-Gama and Joos C. A. M. Buijs. 2017 "Strategies to Automatically Derive A Process Model From A Configurable Process Model Based on Event Data" Preprints. https://doi.org/10.20944/preprints201709.0003.v1
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 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 ERP system, and a real case scenario involving a set of Dutch municipalities.
Keywords
business workflows; discrete event systems; event logs; configurable process models; configurable process trees; process mining; business processes
Subject
Computer Science and Mathematics, Information Systems
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
