Fast and accurate quantitative business process analysis using feature complete queueing models

Sander Peters, Yoav Kerner, Remco Dijkman, Ivo Adan, Paul Grefen

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Quantitative business process analysis is a powerful approach for analyzing timing properties of a business process, such as the expected waiting time of customers or the utilization rate of resources. Multiple techniques are available for quantitative business process analysis, which all have their own advantages and disadvantages. This paper presents a novel technique, based on queueing models, that combines the advantages of existing techniques, in that it leads to accurate analyses, is computationally inexpensive, and feature complete with respect to its support for basic process modeling constructs. An extensive quantitative evaluation has been performed that compares the presented queueing model to existing queueing models from literature. This evaluation shows that the presented model outperforms existing models with one order of magnitude on accuracy. The resulting queueing model can be used for fast and accurate timing predictions of business process models. These properties are useful in optimization scenarios.

Original languageEnglish
Article number101892
JournalInformation Systems
Volume104
DOIs
StatePublished - 1 Feb 2022

Keywords

  • Quantitative business process analysis
  • Queueing models

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Hardware and Architecture

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