Seminar on February 28, 2020

Can Access to Abundant Data Reshape the Theory? Inventory Theory under the Challenge of Data-driven Systems
Nesim K. Erkip, Department of Industrial Engineering, Bilkent University

Abstract

In this talk, I would like to discuss possible effects of having abundant data storage and processing capabilities on decision making for inventory-related problems. I roughly define decision making in between two extremes: On one side, following classical inventory theory, we conceptualize input data and build optimization models to lead us structurally and/or intuitively in decision making. The other extreme is to let the data carry out the decision making under a set of predetermined decision structures. I would like to discuss various possibilities and challenges within the decision making framework limited by the above definition while referring to a limited selection of the current state-of-the-art literature.

Short Bio

Nesim K. Erkip received M.S. and Ph.D. from Stanford University and B.S. from Middle East Technical University (METU), Ankara. Prior to joining Bilkent University in 2005, he worked at METU for over 20 years. He held visiting and research positions at Cornell University, Stanford University, University of California at Berkeley, Eindhoven University of Technology, New York University, and Technical University of Munich. He served as a Fulbright Scholar in the USA during the 1995-96 Academic Year. His main research interest is in multi-echelon inventory theory, distribution systems, supply chains and retailing, as well as applications of OR. He is a founding member of Science and Technology Policy Studies Graduate Program at METU and had been part of several initiatives in preparing reports on “Science and Technology Policy” issues in Turkey during 1990’s. He has been involved in strategic planning activities for non-profit private and public higher educational institutions and served as a member of the Board of Trustees of TED University for several years.

Venue

Friday, February 28, 2020 at 4.00 pm in IE 03