Discovery and Validation of Queueing Networks in Scheduled Processes

  • Arik Senderovich
  • Matthias WeidlichEmail author
  • Avigdor Gal
  • Avishai Mandelbaum
  • Sarah Kadish
  • Craig A. Bunnell
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9097)


Service processes, for example in transportation, telecommunications or the health sector, are the backbone of today’s economies. Conceptual models of such service processes enable operational analysis that supports, e.g., resource provisioning or delay prediction. Automatic mining of such operational models becomes feasible in the presence of event-data traces. In this work, we target the mining of models that assume a resource-driven perspective and focus on queueing effects. We propose a solution for the discovery and validation problem of scheduled service processes - processes with a predefined schedule for the execution of activities. Our prime example for such processes are complex outpatient treatments that follow prior appointments. Given a process schedule and data recorded during process execution, we show how to discover Fork/Join networks, a specific class of queueing networks, and how to assess their operational validity. We evaluate our approach with a real-world dataset comprising clinical pathways of outpatient clinics, recorded by a real-time location system (RTLS). We demonstrate the value of the approach by identifying and explaining operational bottlenecks.


Service Time Service Process Service Policy Schedule Process Process Execution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Arik Senderovich
    • 1
  • Matthias Weidlich
    • 2
    Email author
  • Avigdor Gal
    • 1
  • Avishai Mandelbaum
    • 1
  • Sarah Kadish
    • 3
  • Craig A. Bunnell
    • 3
  1. 1.Technion – Israel Institute of TechnologyHaifaIsrael
  2. 2.Imperial College LondonLondonUK
  3. 3.Dana-Farber Cancer InstituteBostonUSA

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