Drs. Sandra Eksioglu and Burak Eksioglu
Department of Industrial Engineering, Clemson University
March 27, 2015, 2:30 – 3:30 PM
410 John D. Tickle Engineering Building
Dr. Sandra D. Eksioglu is an Associate Professor of Industrial Engineering at Clemson University. She received her PhD in Industrial Engineering from the University of Florida. Prior to joining Clemson, Dr. Eksioglu spent 10 years at Mississippi State University. Dr. Eksioglu’s expertise is in the areas of operations research, network optimization, and algorithmic development. She uses these tools to develop models and solution algorithms for solving large-scale problems that arise in the areas of transportation, logistics, and supply chain. In particular, she is interested in the application of these tools to the bioenergy supply chain. Her research has been funded by the National Science Foundation via an NSF CAREER Award, the US Department of Energy, the US Department of Transportation, MS Department of Transportation, etc. Her research has been published in journals such as, Transportation Science, IIE Transaction, EJOR, Computers & OR, etc. She is an active member of INFORMS, IIE and ASEE.
Optimization Models in Support of Production of Renewable
Co-firing biomass in coal-fired power plants is a strategy that is being used to reduce greenhouse gas emissions. We present a mathematical model that integrates biomass purchasing and transportation costs, plant investment costs, savings due to production tax credit (PTC), and savings from reducing the amount of coal used. The model also captures the loss in process efficiencies due to using biomass, a product which has lower heating value as compared to coal. We formulate the problem as a mixed integer nonlinear program. Next, we provide two linear approximations of this problem which are easier to solve. We use these approximations to derive lower and upper bounds, and conduct extensive numerical analysis to evaluate the quality of these bounds. We develop a case study using data from nine states located in the southeast region of USA. Via our numerical analysis we observe the following: (a) Incentives such as PTC are necessary in order to increase production of renewable energy. (b) The PTC should not be ”one size fits all”. Instead, tax credits could be a function of plant capacity, or the amount of renewable electricity produced. (c) To optimize renewable energy production, the PTC should be customized by region. This is mainly due to the fact that biomass availability differs by regions of US.
Dr. Burak Eksioglu is an associate professor in the Industrial Engineering (IE) Department at Clemson University. He has a Ph.D. from the University of Florida, an M.S. from the University of Warwick, and a B.S. from Bogazici University. Dr. Eksioglu joined the IE faculty at Clemson in August 2014. Prior to joining Clemson, he taught at Mississippi State University. His research program is focused on the area of optimization. Within this area, it spans applications in transportation logistics, production management, supply chain management, graph theory, and linear regression. He uses methodological tools such as Lagrangean relaxation, network programming, primal-dual theory, column generation, meta-heuristics, and game theory in the context of the problem at hand. His research has received funding from a variety of sources. Most of his funding in recent years has come from the U.S. Department of Transportation (USDOT). He has published the results of his research in journals such as the International Journal Production Economics, Computers and OR, OMEGA, Naval Research Logistics, IIE Transactions, OR Letters, and Computers and IE. He is a member of Tau Beta Pi, INFORMS, IIE, ASEE, and POMS.
Optimal Purchasing Strategies with Dual-Sourcing
This paper addresses a procurement issue facing a polystyrene packaging manufacturer considering its optimal purchasing strategies between two suppliers – one providing virgin material, the other offering recycled material. We model a single-period scenario where each supplier sells a product with a known yield distribution at market pricing. The manufacturer must choose whether to sole-source or dual-source, as well as determine how much material to purchase from each supplier to meet deterministic demand. Our results indicate that there is a range of prices from the recycled material supplier where dual-sourcing will lead to higher manufacturer profits compared to sole-sourcing. We show, based on the procurement strategy, the optimal quantities to purchase to maximize manufacturer’s expected profit.