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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New Papers
Babaee Tirkolaee, E., Goli, A., Ghasemi, P., & Goodarzian, F. (2022). Designing a sustainable closed-loop supply chain network of face masks during the COVID-19 pandemic: Pareto-based algorithms. Journal of cleaner production. doi.org/10.1016/j.jclepro.2021.130056
Goodarzian, F., Kumar, V., & Ghasemi, P. (2022). Investigating a citrus fruit supply chain network considering CO2 emissions using meta-heuristic algorithms. Annals of Operations Research. doi.org/10.1007/s10479-022-05005-7
Safaei, S., Ghasemi, P., Goodarzian, F., & Momenitabar, M. (2022). Designing a new multi-echelon multi-period closed-loop supply chain network by forecasting demand using time series model: a genetic algorithm. Environmental Science and Pollution Research, 29(53), 79754-79768. doi.org/10.1007/s11356-022-19341-5
Kusoncum, C., Sethanan, K., Hartl, R. F., & Jamrus, T. (2022). Modified differential evolution and heuristic algorithms for dump tippler machine allocation in a typical sugar mill in Thailand. Operational research, 22(5), 5863-5895. doi.org/10.1007/s12351-020-00597-z
Scherr, Y. O., Hewitt, M., & Mattfeld, D. C. (2022). Stochastic service network design for a platooning service provider. Transportation Research Part C: Emerging Technologies, 144, [103912]. doi.org/10.1016/j.trc.2022.103912