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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Ghasemi, P., Reza Pourhassan, M., Reza Khadem Roshandeh, M., & Sadat Seyed Bathaee, M. (2023). A Multi Echelon Location-Routing-Inventory Model for a Supply Chain Network: NSGA II and Multi-Objective Whale Optimization Algorithm. International Journal of Supply and Operations Management. https://doi.org/10.22034/IJSOM.2023.109996.2804
Heluo, Y., & Robson, C. W. (2023). A note on how public transport announcements affect the spread of COVID-19. Transportation Research Interdisciplinary Perspectives, 21, [100893]. https://doi.org/10.1016/j.trip.2023.100893
Rehsmann, D. (2023). The Sumo coach problem. Review of Economic Design, 27(3), 669-700. https://doi.org/10.1007/s10058-022-00316-4
Babaeinesami, A., Ghasemi, P., & Pourghader Chobar, A. (2023). A Stackelberg Game for Closed-Loop Supply Chains under Uncertainty with Genetic Algorithm and Gray Wolf Optimization. Supply Chain Analytics, [100040]. https://doi.org/10.1016/j.sca.2023.100040
Kinast, A., Braune, R., Dörner, K. F., & Rinderle-Ma, S. (2023). Optimizing the Solution Quality of Metaheuristics Through Process Mining Based on Selected Problems from Operations Research. in C. Di Francescomarino, A. Burattin, C. Janiesch, & S. Sadiq (Hrsg.), Business Process Management Forum - BPM 2023 Forum, Proceedings (S. 232-248). Springer. Lecture Notes in Business Information Processing Band 490 https://doi.org/10.1007/978-3-031-41623-1_14
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