My primary research interest is the applications of Operations Research in solving healthcare problems. My research is supported by:
Sarty, J., Fitzpatrick, EA., Taghavi, M., VanBerkel, P., Hurley, K. (2023) Machine learning to identify attributes that predict patients who leave without being seen in a pediatric emergency department, Canadian Journal of Emergency Medicine, Vol. 25, No. 8, Pages 689–694.
Campbell, J., Taghavi, M., Vanberkel, P. (2023). Day and Night: Locating the general practitioner’s panel after-hours. Applied Sciences: Decision Making with Geo-spatial Information, Vol.13, No. 10, p 6273.
Taghavi, M., Huang, K., Golmohammadi, A. (2021). Polynomial-time algorithms for single resource stochastic capacity expansion models with lost sales. INFOR: Information Systems and Operational Research, 59 (4), 572 - 591
Raine, E., Taghavi, M. (2020). A narrative literature review on human resource planning for palliative care personnel. Indian Journal of Palliative Care,26 (4), 401-404
Taghavi, M., & Huang, K. (2020). A Lagrangian relaxation approach for stochastic network capacity expansion with budget constraints. Annals of Operations Research, 284 (2), 605-621.
Golmohammadi, A., Taghavi, M., Farivar, and N. Azad (2018). Three strategies for engaging a buyer in supplier development Efforts, International Journal of Production Economics (IJPE), 206, 1-14.
Taghavi, M., & Huang, K. (2016). A multi-stage stochastic programming approach for network capacity expansion with multiple sources of capacity. Naval Research Logistics (NRL), 63 (8), 600–614.
Taghavi, M., & Huang, K. (2014). Stochastic Capacity Expansion with Multiple Sources of Capacity. Operations Research Letters, 42 (4), 263-267. (Online Companion)
Taghavi, M., & Shavandi, H. (2012). The P-Center Problem under Uncertainty. Journal of Industrial and Systems Engineering, 6 (1), 48-57.