Welcome to
the Department of Business Decisions and Analytics
The Department of Business Decisions and Analytics is dedicated to high-quality research in quantitative economics and decision support. Building upon a data-driven and optimization-oriented perspective, we develop models and solve complex problems in today’s rapidly changing business environment. We are committed to research-based and competent teaching and try to convey a deep understanding of methods and real-world problems.
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Müller, A-G., & Müller, D. (2023). Problem size reduction methods for large CVRPs. Manuskript zur Veröffentlichung eingereicht.
Choukolaei, H. A., Ghasemi, P., Mirani, S. E., & Heyazi, M. (2023). A GIS-based crisis management using fuzzy cognitive mapping: PROMETHEE approach (a potential earthquake in Tehran). Soft Computing.
Fröhlich, G. E. A., Gansterer, M., & Dörner, K. F. (2023). A rolling horizon framework for the time-dependent multi-visit dynamic safe street snow plowing problem. Networks, 83(2), 236-255. https://doi.org/10.1002/net.22189
Staribacher, D., Rauner, M., & Helmut, N. (2023). Hospital Resource Planning for Mass Casualty Incidents: Limitations for Coping with Multiple Injured Patients. Healthcare : open access journal, 11(20), 1-21. [2713]. https://doi.org/10.3390/healthcare11202713
Fabel, O., Mauser, S., & Zhang, Y. (2023). Performance contests and merit pay with empathic employees. Managerial and Decision Economics, 45(1), 353-372. https://doi.org/10.1002/mde.4003
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