Enriched Workflow Modelling and Stochastic Branch-and-Bound

Autor(en)

Karl Dörner, Walter Gutjahr, Gabriele Kotsis, Martin Polaschek, Christine Strauß

Abstrakt

Workflow systems provide means and techniques for modelling, designing, performing and controlling repetitive (business) processes. The quality of commercial workflow systems is usually determined to a large extent by their versatility and multi-purpose application. One of the current trends in improving workflow systems lies in enriching modelling methods and techniques in order to enlarge design alternatives. The need for such advanced methods is particularly apparent in those fields in which the process duration can be determined only vaguely, but whose completion schedules are at the same time strictly enforced by a highly competitive market by means of fines and penalties. The risk of an overrun has to be weighed against the expected costs and benefits of certain measures reducing turn-around time and their combinations. Because they can help to avoid such penalties ¿ or, at least, keep any potential losses low by identifying critical subprocesses and evaluate appropriate measures ¿ modelling and evaluation techniques are becoming essential features of workflow systems. Methodologically, we use Stochastic Branch-and-Bound as a technique for finding "optimal" bundles of measures. A numerical study shows the benefits of this meta-approach by means of five stepwise-developed decision scenarios requiring rich modelling. Petri nets as a modelling tool and Stochastic Branch-and-Bound as an optimization technique determine for multi-mode resource constrained workflows of varying complexity an optimal workforce strategy with respect to the number of workers and their qualification.

Organisation(en)

Institut für Rechnungswesen, Innovation und Strategie, Institut für Statistik und Operations Research

Externe Organisation(en)

Johannes Kepler Universität Linz

Journal

European Journal of Operational Research

Band

175

Seiten

1798-1817

Anzahl der Seiten

20

ISSN

0377-2217

Publikationsdatum

2006

Peer-reviewed

Ja

ÖFOS 2012

5020 Wirtschaftswissenschaften

Link zum Portal

https://ucris.univie.ac.at/portal/de/publications/enriched-workflow-modelling-and-stochastic-branchandbound(3af85699-5dac-4022-ba95-8e95ae4ea96f).html