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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Burian, M., Köhler, C., Campbell, A. M., & Ehmke, J. F. (2024). Service time window selection for attended home deliveries: a case study for urban and rural areas. Central European Journal of Operations Research, 32(2), 267-294. https://doi.org/10.1007/s10100-023-00879-9
Abbasi, S., & Ghasemi, P. (2024). Supply Chain Network Design Concerning Economy and Environmental Sustainability: Crisis Perspective. Results in Engineering, 22, [102291]. https://doi.org/10.1016/j.rineng.2024.102291
Hess, C., Müller, A-G., Dörner, K. F., & Vigo, D. (2024). Waste collection routing: a survey on problems and methods. Central European Journal of Operations Research, 32(2), 399-434. https://doi.org/10.1007/s10100-023-00892-y
Ferdowsi, A., & Dehghan Chenary, M. (2024). Gain and Pain in Graph Partitioning: Finding Accurate Communities in Complex Networks. Algorithms. https://www.mdpi.com/1999-4893/17/6/226
Goodarzian, F., Ghasemi, P., Appolloni, A., Ali, I., & Cardenas Barron, L. (2024). Supply chain network design based on Big Data Analytics: heuristic-simulation method in a pharmaceutical case study. Production Planning & Control, 1-21. https://doi.org/10.1080/09537287.2024.2344729
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