PhD from Pennsylvania State University
Ronald McGarvey joined the University of Missouri in 2013 with a joint appointment in the Industrial and Manufacturing Systems Engineering Department and at the Harry S Truman School of Public Affairs. His primary research interest is in applied optimization and its applications to public policy and resource management.
McGarvey has more than 10 years of experience working as a researcher in Project AIR FORCE, a federally funded research and development center operated by the RAND Corporation that is tasked with performing policy analysis on behalf of Air Force leadership.
PubAf 8001: Public Sector Operations Research
PubAf 8185: Research Methods and Inquiry in Public Affairs (mid-career, online)
Karakose G, McGarvey RG. Optimal detection of critical nodes: improvements to model structure and performance. To appear (accepted June 2018), Networks and Spatial Economics.
Karakose G, McGarvey RG.. Optimal K-node disruption on a node-capacitated network. To appear (accepted April 2018), Optimization Letters.
Dundar B, McGarvey RG, Aguilar FX. A robust optimisation approach for identifying multi-state collaborations to reduce CO2 emissions. To appear (accepted March 2018), Journal of the Operational Research Society.
Thorsen A, McGarvey RG (2018), Efficient frontiers in a frontier state: Viability of mobile dentistry services in rural areas. European Journal of Operational Research, 268, 1062-1076.
Birisci E, McGarvey RG (2018), Optimal production planning utilizing leftovers for an all-you-care-to-eat food service operation. Journal of Cleaner Production, 171, 984-994.
Karakose G, McGarvey RG (2018), Capacitated path-aggregation constraint model for arc disruption in networks. Transportation Research Part E, 109, 225-238.
Karakose G, McGarvey RG (2018), Node-securing connectivity-based model to reduce infection spread in contaminated networks. Computers & Industrial Engineering, 115, 512-519.
McGarvey RG (2018), When to call on an advantageous restart option. Journal of Sports Analytics, 4, 133-143.