Welcome to the Department of Business Analytics and Decision Making
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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Taverna, F., & Tilk, C. (2026). Enhancing Waste Collection: A Branch-and-Cut-and-Price approach for the Periodic Vehicle Routing Problem with Intermediate Facilities applied to a real-world case study. European Journal of Operational Research, 331(2), 601-614. https://doi.org/10.1016/j.ejor.2025.09.039
Dragone, D., Feichtinger, G., Grass, D., Hartl, R. F., Kort, P. M., Seidl, A., & Wrzaczek, S. (2026). Obesity, sedentary behavior and lifestyle: A lifecycle model of eating and physical activity. Journal of Health Economics, 106, Artikel 103114. https://doi.org/10.1016/j.jhealeco.2026.103114
Lyu, X., Tierney, K., & Schulte, F. (2026). Collaborative maritime and port transportation: A literature review. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2026.01.041
Ahadzadeh, R., Dehghani, E., & Ghasemi, P. (2026). Towards sustainable closed-loop photovoltaic supply chains: A hybrid framework integrating reinforcement learning and mathematical models. Expert systems with applications, 296(D), Artikel 129182. https://doi.org/10.1016/j.eswa.2025.129182
Goodarzian, F., Abraham, A., Muñuzuri , J., Taghipour, A., & Ghasemi, P. (2026). A Benders decomposition approach for a new sustainable pharmaceutical supply chain network: a case study in France. Annals of Operations Research, 356(2-3), 881-919. https://doi.org/10.1007/s10479-024-05936-3
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