The course focuses on the strategic role of the supply chain, key drivers of supply chain performance, and analytical methods for supply chain analysis. Possible topics include inventory planning and management, sourcing, transporting, and pricing products, supply chain network design, and coordination and value of information in a supply chain. Prerequisites: MGTSC 312 and OM 352.Winter Term 2022
This course will provide an in-depth introduction to a particular methodology or a particular setting that is relevant to research in operations management. The topic may vary from year to year. Possible topics include optimization modeling and formulation, stochastic modeling and optimization, behavioural research in operations management, and health care operations management. The required background for students will vary depending on the topic. This course may be appropriate for some graduate students in engineering or computing science. Prerequisite: Written permission of the instructor. Approval of the Business PhD Program Director is also required for non-PhD students.Winter Term 2022
• Rastpour, A., A. Ingolfsson, B. Kolfal, 2020, “Modeling Yellow and Red Alert Durations for Ambulance Systems,” Production and Operations Management, 29(8), pp. 1972-1991.
• Delasay, M., A. Ingolfsson, B. Kolfal, and K. Schultz, 2019, “Load Effect on Service Times,” European Journal of Operational Research, 279(3), pp. 673-686.
• Soltani, M., M. Samorani, and B. Kolfal, 2019, “Appointment Scheduling with Multiple Providers and Stochastic Service Times,” European Journal of Operational Research, 277(2), pp. 667-683.
• Sun, C., Y. Ji, B. Kolfal, and R. Patterson, 2017, “Business-To-Consumer Platform Strategy: How Vendor Certification Changes Platform and Seller Incentives,” ACM Transactions on Management Information Systems, 8(2-3), Article No. 6, DOI: https://doi.org/10.1145/3057273.
• Delasay, M., A. Ingolfsson, and B. Kolfal, 2016, “Modeling Load and Overwork Effects in Queueing Systems with Adaptive Service Rates,” Operations Research, 64(4), pp. 867–885.
• Alanis, R., A. Ingolfsson, and B. Kolfal, 2013, “A Markov Chain Model for an EMS System with Repositioning,” Production and Operations Management, 22(1), pp. 216-231.
• Kolfal, B., R. Patterson, and L. Yeo, 2013, “Market Impact on IT Security Spending,” Decision Sciences Journal, 44(3), pp. 517-556.
• Iravani, S.M.R., B. Kolfal, and M.P. Van Oyen, 2012, “Process Flexibility and Inventory Flexibility via Product Substitution,” Flexible Services & Manufacturing, 26(3), pp. 320-343.
• Delasay, M., B. Kolfal, and A. Ingolfsson, 2012, “Maximizing Throughput in Finite-Source Parallel Queue Systems,” European Journal of Operational Research, 217(3), pp. 554-559.
• Saghafian, S., M.P. Van Oyen, and B. Kolfal, 2011, “The ‘W’ Network and the Dynamic Control of Unreliable Flexible Servers,” IIE Transactions, 43(12), pp. 893-907.
• Iravani, S.M.R., B. Kolfal, and M.P. Van Oyen, 2011, “Capability Flexibility: A Decision Support Methodology for Parallel Service and Manufacturing Systems with Flexible Servers,” IIE Transactions, 43(5), pp. 363-382.
• Saghafian, S., M.P. Van Oyen, and B. Kolfal, 2009, “A New Policy for the Control of Parallel Queueing Systems,” Proceedings of 2009 NSF Engineering Research and Innovation Conference, Honolulu, Hawaii.
• Iravani, S.M.R., B. Kolfal, and M.P. Van Oyen, 2007, “Call Center Labor Cross-Training: It’s a Small World After All,” Management Science, 53(7), pp. 1102-1112.
• Iravani, S.M.R., and B. Kolfal, 2005, “When Does the cμ Rule Apply to Finite-Population Queueing Systems,” Operations Research Letters, 33(3), pp. 301-304.
• Hidaji, Hooman, Kolfal, Bora, Nault, Barrie, Patterson, Raymond, Rolland, Eric, Yeo, Lisa, 2020, “Service Disruptions and Provider Choice.”
• Ding, Likang, Kolfal, Bora, Ingolfsson, Armann, 2020, “The relationship between expected service times and service rates for state-dependent queues.”