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Modeling and Solution Methods for a Class of Stochastic Programming Problems under Endogenous Observation of Uncertainty

We first present an overview of optimization problems under uncertainty and multi-stage stochastic programming methods. We then discuss applications where the decision maker alters the underlying stochastic process by affecting the timing of uncertainty observation, i.e. a special class of problems under endogenous uncertainty. We discuss how this important but less studied class of problems can be formulated as a large-scale multi-stage stochastic programming model. To address this challenging problem, we develop a number of theoretical results, modeling methods and computational techniques. First, we develop a number of properties that exploit the structure of the problem and allow us to formulate substantially smaller yet tighter models. Second, we discuss a reduced formulation where a subset of nonanticipativity constraints are relaxed and a finite-horizon approximation that can be used in rolling-horizon approach that yields solutions of high quality. Third, we present a novel branch-and-cut algorithm where we start from a reduced model and add essential constraints only if they are violated. The presented methods are applied to the planning of clinical trials in the pharmaceutical research and development pipeline.

Type of Seminar:
Public Seminar
Prof. Christos T. Maravelias
Department of Chemical and Biological Engineering, University of Wisconsin-Madison, WI USA.
May 20, 2009   11:15

ETH Zentrum, Building ETZ, Room E 9
Contact Person:

Prof. M. Morari
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Biographical Sketch:
Christos was born on 1973 in Athens, Greece. He obtained his Diploma in Chemical Engineering from the National Technical University of Athens in 1996. Next, he moved to the London School of Economics (London, UK), where he received an MSc in Operations Research in 1997. After completing his military service in Greece, he went to Carnegie Mellon University (Pittsburgh, USA) where he started his doctoral studies under the supervision of Professor Ignacio Grossmann. In the fall of 2004 he joined the faculty of the Department of Chemical and Biological Engineering at the University of Wisconsin – Madison as an assistant professor. He is a recipient of a NSF CAREER award and the 2008 David Smith Jr. Award from the CAST Division of AIChE. Christos’ research interests are in the areas of a) production planning and scheduling, b) stochastic programming for research and development pipeline management, and c) process synthesis.