ISE Spring Seminar: Melda Ormeci Mato, Ph.D. & John Vande Vate, Ph.D.


10:40 am-11:30 am
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UF ISE Spring Seminar Series

4/7/23 at 10:40 AM

Virtual Seminar

Title: On the Optimality of Stepwise Policies

Abstract: We consider the problem of simultaneously managing capacity, inventory and backorders in a multi-mode production environment modeled via Brownian motion. The presence of more than two production modes adds an additional level of complexity: not just when to change modes, but also which mode to change to. This paper addresses that complexity by answering the question of when natural policies that move stepwise from one mode to the next faster or the next slower mode are optimal. We show that, under the two assumptions that demand is the overriding source of variability in the process and that the cost to change from one production mode to another is proportional to the difference in the production capacities, a policy that moves stepwise among the modes minimizes the long-run average cost. Examples demonstrate that if either assumption is violated no policy that moves stepwise among the modes may be optimal. To focus on the complexity of identifying when to change modes and which mode to change to, we restrict our model to simple convex holding and backorder costs and linear processing costs and costs for rejecting demand and idling capacity. We adopt the economic average cost model of Ormeci Matoglu et al. (2019) that allows the manager to reject demand or idle capacity at any time and confirm their characterization of the economic boundaries of an optimal policy. We show that under the economic average cost model a production mode that is initially unattractive may later become attractive as new modes are added. To address this, we introduce new methods for determining whether adding a new production mode will reduce the long-run average cost and for finding an optimal policy when it does. Our arguments are constructive and lead to a practical algorithm for finding an optimal when our two assumptions hold.


Melda Ormeci Matoglu is an Assistant Professor at Peter T. Paul College of Business and Economics at the University of New Hampshire. Her research interests span both fields of optimization and stochastic control, with applications mainly within the areas of supply chain management and logistics. Her work covers theoretical problems dealing with optimal stochastic control of Brownian motion along with practical applications of these problems. Her work on supply chain problems is mainly related to inventory and capacity management. Her research is published in Operations Research, Stochastic Systems, Annals of Operations Research, Journal of Operational Research, Advances in Applied Probability.

John Vande Vate is a professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Institute of Technology. He was the founder and executive director of Georgia Tech’s Executive Master’s in International Logistics and Supply Chain Strategy (EMIL-SCS) program and has held visiting positions at MIT Sloan School of Management, Carnegie Mellon Tepper School of Business, University of Pittsburgh, Department of Economics, among others. During the past 40 years, he has consulted for a variety of companies on a range of management science applications. His research has been published in Econometrica, Mathematics of Operations Research, Operations Research, Discrete Applied Mathematics, Journal of Combinatorial Theory, Mathematical Programming, Questa, Advances in Applied Probability, Journal of Theoretical Biology, Mechanics of Structures and Machines, and other established journals. He served on the board of the Supply Chain Council as the global treasurer and was named among Supply & Demand Chain Executive’s Pros to Know in 2006. Dr. Vande Vate was among a team that received the 2016 Golden Goose Award.

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Industrial & Systems Engineering