Events Calendar

Astani CEE Ph.D. Seminar

Speaker: Bita Analui, Ph.D., , Institute of Statistics and Operations Research, University of Vienna, Austria

Talk Title: Multistage Stochastic Optimization Problems under Model Uncertainty

Abstract:
Multistage Stochastic Optimization is a well-established framework where uncertainty is involved and decisions have to
be taken in a sequential manner only based on the available information at the time of decision making. These two
characteristics are enough to tie multistage stochastic optimization into almost all decision problems in the real life.
However, in addition to parameters’ uncertainty, in the class of real world problems, the true probability model, which describes these parameters, is itself subject to uncertainty that should not be ignored. Acknowledging the incomplete information about the underlying probability model in multistage stochastic optimization problems, leads to the following questions:

• How can we account for model uncertainty when solving a multistage stochastic program?
• What are the associated theoretical and algorithmic complexities?

In this talk a new theoretical foundation and a non-parametric approach provide answers to these questions and can be
used in a wide range of applications. In this regard, the model uncertainty problem is formulated in a minimax form and a
setup is given for studying saddle point properties of the multistage stochastic minimax problems. Moreover, an
algorithmic approach for finding the minimax decisions at least asymptotically is presented. In addition, by considering
the objective as a function of robustness, the distributionally robust frontier is drawn and costs and rewards of robustness around this frontier is quantified. Finally, this approach for a short term hydro electricity production problem with weekly ordering under weather and market risk is implemented. The worst model is found within the corresponding ambiguity neighborhood and a solution which is robust with respect to the model uncertainty is determined.



Biography: Bita Analui received her MS from University of Sheffield in 2009, with research focus on statistics and her
PhD from University of Vienna in 2014, where she won a scholarship to conduct research at Computational Optimization
Doctoral College. Her primary research focus is algorithms and applications of Multistage Stochastic Optimization (MSO)
problems. Simultaneously, she worked with Siemens Austria in designing and implementing solution algorithms and
performing sensitivity analysis in the field of ‘Stochastic optimization in power systems’.

Location: Seeley G. Mudd Building (SGM) - 101

Audiences: Everyone Is Invited

Contact: Evangeline Reyes