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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Alarcon Ortega, E. J., & Dörner, K. F. (2023). A sampling-based matheuristic for the continuous-time stochastic inventory routing problem with time-windows. Computers & Operations Research, 152, [106129]. https://doi.org/10.1016/j.cor.2022.106129
Guo, S., & Vetschera, R. (2023). Preference Reversals in Dynamic Decision-making Under Uncertainty Based on Regret Theory. Managerial and Decision Economics, 44(3), 1720-1731. https://doi.org/10.1002/mde.3778
Haferkamp, J., Ulmer, M. W., & Ehmke, J. F. (2023). Heatmap-Based Decision Support for Repositioning in Ride-Sharing Systems. Transportation Science. https://doi.org/10.1287/trsc.2023.1202
Goodarzian, F., Ghasemi, P., Gonzalez, E. DR. S., & Tirkolaee, E. B. (2023). A sustainable-circular citrus closed-loop supply chain configuration: Pareto-based algorithms. Journal of Environmental Management, 328, [116892]. https://doi.org/10.1016/j.jenvman.2022.116892
Parhi, S., Joshi, K., & Akarte, M. (2023). Decision-making in smart manufacturing: A framework for performance measurement. International Journal of Computer Integrated Manufacturing, 36(2), 190-218. https://doi.org/10.1080/0951192X.2022.2048420
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