Ramez Kian is a Lecturer in the Department of Management. His main roles are delivering courses and supervision of PhD and Master’s students in their research projects. He is experienced in applying mathematical modelling and operational research techniques to develop business solutions for problems mainly in operation management, supply chain and logistics area.
International & Previous Work Experiences
He started his career in 2008 as a logistics expert in automotive industry in Iran. In 2010 he moved to Turkey and pursued his PhD studies on sustainable production planning. Between 2015 and 2016 he was employed by University of Southampton and carried out research in collaboration with three universities and four companies regarding optimisation of maintenance scheduling in maritime sector. He was employed with Istanbul Bilgi University (Turkey) and University of Tabriz (Iran) between 2016 and 2018 conducting three research papers on the area of supply chain management and logistics. He has been with Nottingham Trent University since 2018 as a Research Fellow working on a funded research project about a large-scale distribution network optimisation of the cash-based-interventions for Syrian refugees in Turkey; and he is now a Lecturer in Operations Management and Logistics in Nottingham Business School.
- 2019-now: Lecturer in Operations Management and Logistics
- 2018-2019: Research Fellow in Nottingham Trent University (UK)
- 2017-2019: Visiting Researcher in University of Tabriz (Iran)
- 2016-2017: Assistant Professor in Istanbul Bilgi University (Turkey)
- 2015-2016: Research Fellow in Southampton Business School (UK)
- 2010-2015: Teacher and Research Assistant in Bilkent University (Turkey)
- 2008-2010: Logistics and Supply chain analyst in IKCO (Automotive manufacturer, Iran)
- Optimisation (Mixed integer, Nonlinear, Heuristics)
- Logistics and Supply Chain Management
- Production planning
Ongoing collaboration on research with overseas universities.
- Kian, R. (2020). A production planning problem with lost sales and nonlinear convex production cost function under carbon emission restrictions. Journal of Energy Management and Technology, 4(2), 1-13.
- Kian, R., Berk, E., & Gürler, Ü. (2019). Minimal conic quadratic reformulations and an optimization model. Operations Research Letters,47(6), 489-493.
- Ghahremani-Nahr, J., Kian, R., & Sabet, E. (2019). A robust fuzzy mathematical programming model for the closed-loop supply chain network design and a whale optimization solution algorithm. Expert Systems with Applications, 116, 454-471.
- Sabet, E., Yazdani, B., Kian, R., & Galanakis, K. (2019). A strategic and global manufacturing capacity management optimisation model: A scenario-based multi-stage stochastic programming approach. Omega.
- Kian, R., Bektaş, T., & Ouelhadj, D. (2019). Optimal spare parts management for vessel maintenance scheduling. Annals of operations research, 272(1-2), 323-353.
- Allahi, F., De Leeuw, S., Sabet, E., Kian, R., Damiani, L., Giribone, P., ... & Cianci, R. (2018). A review of system dynamics models applied in social and humanitarian research.
- Ghahremani Nahr, J., Kian, R., & Rezazadeh, H. (2018). A modified priority-based encoding for design of a closed-loop supply chain network using a discrete league championship algorithm. Mathematical Problems in Engineering, 2018.
- Kian, R., & Kargar, K. (2016). Comparison of the formulations for a hub-and-spoke network design problem under congestion. Computers & Industrial Engineering, 101, 504-512.
- Kian, R., Berk, E., & Gürler, Ü. (2014). An Integrated Replenishment and Transportation Model. Global Logistics Management, CRC Press (pp. 795-814).
- Kian, R., Gürler, Ü., & Berk, E. (2014). The dynamic lot-sizing problem with convex economic production costs and setups. International Journal of Production Economics, 155, 361-379.
- Rabbani, M., Ahmadi, G., & Kian, R. (2009, July). A new comprehensive framework for ranking accepted orders and supplier selection in make-to-order environments. In 2009 International Conference on Computers & Industrial Engineering (pp. 919-924). IEEE.