CSCE 689: Special Topics in Stochastic & Risk-averse Optimization

Fall 2011

Optimization has played a key role in making the task of decision making from art to science in the past century. An important challenge that still remains is our ability to incorporate the uncertainty in our knowledge and risk-aversion in our objective. A simple but insightful example of this is encapsulated in the decision question: given a number of route choices, which shall I choose? This simple question (easily solvable in a deterministic setting) becomes highly non-trivial when we incorporate the uncertainty of delays and the individual's risk-aversion.

This graduate seminar will survey the state-of-art in optimization under uncertainty, with an emphasis on algorithms and risk-averse modeling in combinatorial settings. Sample topics include: Von Neumann-Morgenstern expected utility theory, Coherent measures of risk, Two-stage and multistage stochastic optimization, Robust optimization, Models with probabilistic constraints, Statistical inference, Risk-averse optimization.

Course Information

Course Outline

There is a significant dynamic component to the course, as topics drop in and out, or get longer or shorter treatment, depending on audience interest/reaction/resistence. Given this, here is a rough outline of the course material:


Online Resources

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