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Optimal Paths in Business Processes: Framework and Applications

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Business Process Management Workshops (BPM 2017)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 308))

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Abstract

We present an innovative framework for calculating optimal execution paths in business processes using the abstraction of workflow hypergraphs. We assume that information about the utility associated with the execution of activities in a process is available. Using the workflow hypergraph abstraction, finding a utility maximising path in a process becomes a generalised shortest hyperpath problem, which is NP-hard. We propose a solution that uses ant-colony optimisation customised to the case of hypergraph traversal. We discuss three possible applications of the proposed framework: process navigation, process simulation, and process analysis. We also present a brief performance evaluation of our solution and an example application.

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Notes

  1. 1.

    Code available at: https://github.com/emettelatripla/opsupport.

  2. 2.

    http://murali-group.github.io/halp/.

  3. 3.

    Available at: https://data.4tu.nl/repository/collection:event_logs.

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Authors and Affiliations

  1. Ulsan National Institute of Science and Technology (UNIST), 50 UNIST-gil, Ulju-gun, Ulsan, 44919, Republic of Korea

    Marco Comuzzi

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  1. Marco Comuzzi
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Correspondence to Marco Comuzzi .

Editor information

Editors and Affiliations

  1. Department of Service and Information System Engineering, Universitat Politècnica de Catalunya, Barcelona, Spain

    Ernest Teniente

  2. Humboldt-Universität zu Berlin, Berlin, Berlin, Germany

    Matthias Weidlich

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Comuzzi, M. (2018). Optimal Paths in Business Processes: Framework and Applications. In: Teniente, E., Weidlich, M. (eds) Business Process Management Workshops. BPM 2017. Lecture Notes in Business Information Processing, vol 308. Springer, Cham. https://doi.org/10.1007/978-3-319-74030-0_7

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  • DOI: https://doi.org/10.1007/978-3-319-74030-0_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-74029-4

  • Online ISBN: 978-3-319-74030-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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