Dr Bahman Rostami-Tabar

2023

• Rostami-Tabar, B., Goltsos, T. E. and Shixuan, W. 2023. Forecasting for lead-time period by temporal aggregation: Whether to combine and how. Computers in Industry 145, article number: 103803. (10.1016/j.compind.2022.103803)

2022

• Rostami-Tabar, B., Hasni, M. and Babai, Z. 2022. On the inventory performance of demand forecasting methods of medical items in humanitarian operations. IFAC-PapersOnLine 55(10), pp. 2737-2742. (10.1016/j.ifacol.2022.10.132)
• Babaveisi, V., Teimoury, E., Gholamian, M. R. and Rostami-Tabar, B. 2022. Integrated demand forecasting and planning model for repairable spare part: an empirical investigation. International Journal of Production Research
• Gartner, D., Viana, J., Rostami-Tabar, B., Pförringer, D. and Edenharter, G. 2022. Challenging the throwaway culture in hospitals: scheduling the mix of reusable and single-use bronchoscopes. Journal of the Operational Research Society (10.1080/01605682.2022.2129490)
• Rostami-Tabar, B. and Ziel, F. 2022. Anticipating special events in emergency department forecasting. International Journal of Forecasting 38(3), pp. 1197-1213. (10.1016/j.ijforecast.2020.01.001)
• Rostami-Tabar, B., Ali, M. M., Hong, T., Hyndman, R. J., Porter, M. D. and Syntetos, A. 2022. Forecasting for social good. International Journal of Forecasting 38(3), pp. 1245-1257. (10.1016/j.ijforecast.2021.02.010)
• Petropoulos, F. et al. 2022. Forecasting: theory and practice. International Journal of Forecasting 38(8), pp. 705-871. (10.1016/j.ijforecast.2021.11.001)
• Rostami-Tabar, B., Babai, Z. and Syntetos, A. 2022. To aggregate or not to aggregate: Forecasting of finite autocorrelated demand. Journal of the Operational Research Society (10.1080/01605682.2022.2118631)
• Rostami-Tabar, B. and Boylan, J. 2022. Forecasting and its Beneficiaries. In: Salhi, S. and Boylan, J. eds. The Palgrave Handbook of Operations Research. Palgrave Macmillan, pp. 695-717., (10.1007/978-3-030-96935-6_21)
• Rostami-Tabar, B., Hong, T. and Porter, M. D. 2022. Guest Editorial: Forecasting for social good. International Journal of Forecasting 38(3), pp. 1173-1174.
• Abolghasemi, M., Rostami-Tabar, B. and Syntetos, A. 2022. The value of point of sales information in upstream supply chain forecasting: an empirical investigation. International Journal of Production Research (10.1080/00207543.2022.2063086)
• Mircetic, D., Rostami-Tabar, B., Nikolicic, S. and Maslaric, M. 2022. Forecasting hierarchical time series in supply chains: an empirical investigation. International Journal of Production Research 60(8), pp. 2514-2533. (10.1080/00207543.2021.1896817)
• Babai, M. Z., Boylan, J. E. and Rostami-Tabar, B. 2022. Demand forecasting in supply chains: a review of aggregation and hierarchical approaches. International Journal of Production Research 60(1), pp. 324-348. (10.1080/00207543.2021.2005268)
• Wang, Z., Rostami-Tabar, B., Haider, J. J. and Naim, M. 2022. A systematic literature review of trauma networks and systems: from operations management perspectives. Presented at: 12th European Decision Sciences Conference, Dublin, Ireland, 29 May – 1 June 2022.

2021

• Rostami-Tabar, B. 2021. Business forecasting in developing countries. In: Gilliland, M., Tashman, L. and Sglavo, U. eds. Business forecasting : the emerging role of artificial intelligence and machine learning. Wiley and SAS Business Series
• Rostami-Tabar, B. and Rendon-Sanchez, J. F. 2021. Forecasting COVID-19 daily cases using phone call data. Applied Soft Computing 100, article number: 106932. (10.1016/j.asoc.2020.106932)

2019

• Rostami-Tabar, B., Babai, M. Z., Ali, M. and Boylan, J. E. 2019. The impact of temporal aggregation on supply chains with ARMA(1,1) demand processes. European Journal of Operational Research 273(3), pp. 920-932. (10.1016/j.ejor.2018.09.010)

2017

• Kourentzes, N., Rostami-Tabar, B. and Barrow, D. K. 2017. Demand forecasting by temporal aggregation: Using optimal or multiple aggregation levels?. Journal of Business Research 78 (10.1016/j.jbusres.2017.04.016)
• Rostami-Tabar, B. and Disney, S. M. 2017. The bullwhip effect under count time series: The case of first order integer auto-regressive demand processes. Presented at: International Symposium on Industrial Engineering and Operations Management, Bristol, UK, 25-26 July 2017.
• Rostami-Tabar, B. and Disney, S. M. 2017. The impact of temporal aggregation on production and inventory costs. Presented at: OR59 Annual Conference, Loughborough, United Kingdom, 12-14 September 2017.

2016

• Emrouznejad, A., Rostami-Tabar, B. and Petridis, K. 2016. A novel ranking procedure for forecasting approaches using data envelopment analysis. Technological Forecasting and Social Change 111, pp. 235-243. (10.1016/j.techfore.2016.07.004)

2015

• Rostami-Tabar, B., Babai, M. Z., Ducq, Y. and Syntetos, A. 2015. Non-stationary demand forecasting by cross-sectional aggregation. International Journal of Production Economics 170(Part A), pp. 297-309. (10.1016/j.ijpe.2015.10.001)

2014

• Rostami-Tabar, B., Babai, M. Z., Syntetos, A. and Ducq, Y. 2014. A note on the forecast performance of temporal aggregation. Naval Research Logistics 61(7), pp. 489-500. (10.1002/nav.21598)

2013

• Rostami-Tabar, B., Babai, M. Z., Syntetos, A. and Ducq, Y. 2013. Demand forecasting by temporal aggregation. Naval Research Logistics 60(6), pp. 479-498. (10.1002/nav.21546)

2008

• Amin-Naseri, M. and Rostami-Tabar, B. 2008. Neural network approach to lumpy demand forecasting for spare parts in process industries. Presented at: International Conference on Computer and Communication Engineering, 13-15 May 20082008 International Conference on Computer and Communication Engineering Proceedings. IEEE pp. -., (10.1109/ICCCE.2008.4580831)
• Nasiri Pour, A., Rostami-Tabar, B. and Rahimzadeh, A. 2008. A hybrid neural network and traditional approach for forecasting lumpy demand. Proceedings of the World Academy of Science, Engineering and Technology 2(4)