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.
News
Teaching
Research
21.07.2021
New Papers
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Goodarzian, F., Ghasemi, P., & Gunasekaren, A. (2023). A fuzzy sustainable model for COVID-19 medical waste supply chain network. Fuzzy Optimization and Decision Making. https://doi.org/10.1007/s10700-023-09412-8
Momenitabar, M., Ebrahimi, Z. D., Bengtson, K., Helmi, W., & Ghasemi, P. (2023). An integrated machine learning and quantitative optimization method for designing sustainable bioethanol supply chain networks. Decision Analytics Journal, 7, [100236]. https://doi.org/10.1016/j.dajour.2023.100236
Krebs, C., & Ehmke, J. F. (2023). Solution validator and visualizer for (combined) vehicle routing and container loading problems. Annals of Operations Research. https://doi.org/10.1007/s10479-023-05238-0
Matsatsinis, N., & Vetschera, R. (2023). Editorial for the Feature Cluster on OR and Analytics in the Era of Digital Transformation – Selected papers from EURO 2021. European Journal of Operational Research, 306(3), 999-1000. https://doi.org/10.1016/j.ejor.2022.11.026
Florio, A. M., Gendreau, M., Hartl, R. F., Minner, S., & Vidal, T. (2023). Recent advances in vehicle routing with stochastic demands: Bayesian learning for correlated demands and elementary branch-price-and-cut. European Journal of Operational Research, 306(3), 1081-1093. https://doi.org/10.1016/j.ejor.2022.10.045
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