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Title : Next Generation Business Applications for Radio Frequency Identification
Date : April 28, 2008
Speaker : Diego Klabjan, Associate Professor
Affiliation : Department of Industrial Engineering and Management Sciences, Northwestern University
Abstract
Radio frequency identification is moving from early stages of slap-and-ship to integration with existing systems and business applications. It is the latter that will yield a return on investment. In addition to existing business applications such as promotions execution we discuss in details two new novel applications. Return of investment is easier to achieve by exploiting new business process. One such process is expediting. We consider a serial system with the option of expediting outstanding orders from intermediate installations. We also assume that goods have an expiry date.
We introduce so-called sequential systems, which have nicely structured policies. The regular and expediting orders follow a base stock type policy. As the second application, we study the radio frequency identification deployment on a logistics network. The benefits of this new technology are assumed to come from a reduction in lost items. We develop a model for deployment and provide managerial insights.
Biosketch
Diego Klabjan is an associate professor at Northwestern University, Department of Industrial Engineering and Management Sciences. After obtaining his doctorate from the School of Industrial and Systems Engineering of the Georgia Institute of Technology in 1999, in the same year he joined the University of Illinois at Urbana-Champaign. In 2007 he became an associate professor at Northwestern. He is the recipient of the first prize of the 2000 Transportation Science Dissertation Award and he received various other awards with graduate students. He is a former president of the INFORMS Aviation Applications Section. He is an associate editor for Naval Research Logistics and two areas in Operations Research. His research is focused on transportation, supply chain management, radio frequency identification, and large-scale optimization.
