A Robust Control Approach to Optimizing Production, Inventory and Transportation

Daniel J. Epstein Department of Industrial and Systems Engineering Seminar - ISE 650Guest Speaker: Thomas Marlin - Department of Chemical Engineering, McMaster UniversityABSTRACT: Recently, advances in computing and optimization algorithms have lead to a renewed interest in analyzing logistics systems with the recognition that (1) substantial uncertainties exist in their dynamic behavior and (2) periodic re-optimization (rolling horizon optimization) affects the future behavior. The Model-Predictive Control (MPC) structure is ideal for modeling these closed-loop logistics systems. This talk will introduce the concept of robust model-predictive control of uncertain systems and how it can be implemented in real-time. Challenges in formulation and computation will be introduced, and proposals for a computationally tractable approach presented. Application to a simple (but real) industrial logistics problem will be presented. The problem has several manufacturing steps with intermediate inventory and transportation to regional distribution outlets. Uncertainty occurs in manufacturing times, transportation times, and customer demands. The goal is to reduce holding (inventory) costs while preventing backorders, where possible. The behavior of the system under various control approaches will be compared, and the advantages of a robust approach quantified.This work has been performed in conjunction with Adam Warren and Xiang Li at McMaster University.THURSDAY, APRIL 16, 2009, GERONTOLOGY BUILDING (GER) ROOM 309, 1:00 – 2:00 PM----------------BIO: Tom Marlin joined the Department of Chemical Engineering at McMaster University in Hamilton, Ontario, Canada, as NSERC Research Professor in Industrial Process Control in 1988. He received his Ph.D. from the University of Massachusetts in 1972; then, he practiced engineering for 15 years in the chemical and petroleum industries. In 1987, he served as the Visiting Fellow, for the Warren Centre Study located at the University of Sydney, Australia. During the one-year project, a team of over 40 academics and practitioners investigated methods for quantifying benefits from automation; the results of this project were published in a manuscript. From 1988 until 2007, Dr. Marlin served as the Director of the McMaster Advanced Control Consortium (MACC), which develops relevant research through collaboration among university researchers and numerous companies. MACC consists of five professors, 12 industrial members and 25 university researchers, principally graduate students and post-doctoral fellows. He teaches university courses in process control, process analysis, problem solving, and optimization and has published a textbook in process control (Process Control, Designing Process and Control Systems for Dynamic Performance 2nd Ed., McGraw-Hill, 2000). In addition, he presents industrial short courses on process control, automation benefits, and optimization. Dr. Marlin's research interests focus on improved performance of dynamic systems through real-time operations optimization and process control design.Email: marlint@mcmaster.caPersonal WEB: http://www.chemeng.mcmaster.ca/faculty/marlin/Consortium: http://www.macc.mcmaster.ca/

Location: Ethel Percy Andrus Gerontology Center (GER) - 309

Audiences: Everyone Is Invited

Contact: Georgia Lum