Baumann, Fabian

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Baumann
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Fabian
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Fabian Baumann

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2021 - 20232

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Gerade angezeigt 1 - 2 von 2
  • Kein Vorschaubild vorhanden
    Publikation
    Supporting reuse of business process models by semantic annotation
    (Springer, 2023) Baumann, Fabian; Hinkelmann, Knut; Montecchiari, Devid
    Business Process Management (BPM) is a widely applied discipline in many organizations. Creating and maintaining business process models is a task that still requires much human work and is costly and cumbersome. The reuse of business process models is a solution to minimize human effort and increase quality. For reuse, appropriate process models must be discovered in a repository. Enrichment of the models with semantic annotations from domain ontologies can leverage better results for of discovering reusable process models. Although using semantically annotated business process models for the case of reuse has been mentioned and proposed in the literature, the exact requirements and implementation have yet to be analyzed in detail. This paper closes this research gap with an artifact in the form of a methodology to discover business process models. This includes a list of relevant criteria, a base ontology, possible automated annotation techniques, and a query form.
    04B - Beitrag Konferenzschrift
  • Kein Vorschaubild vorhanden
    Publikation
    Multiobjective optimization of the train staff planning problem using NSGA-II
    (ACM, 2021) Girardin, Simon; Baumann, Fabian; Dornberger, Rolf; Hanne, Thomas
    The optimization problem of assigning train staff to scheduled train services is called the train staff planning problem. A part of this is the rostering with the aim to create a duty timetable under the consideration of different constraints, preferences etc. The problem is formulated as a biobjective problem considering costs and penalties for violating constraints. In this paper, we analyze the application of the nondominated sorting genetic algorithm II (NSGA-II) for multiobjective optimization in order to propose a solution to the considered train staff planning problem. Numerical experiments are conducted using several example problems. These experiments provide suitable parameters for using NSGA-II and further insights into the adaptation of this algorithm to the problem under consideration.
    04B - Beitrag Konferenzschrift