Rüdiger Schultz

CORS/INFORMS International Conference

Montreal, Canada

June 2015


“Go West, young man, get yourself involved in planning under uncertainty.” In an interview in 1999 George Dantzig said that this probably would have been his message to the INFORMS crowd that was to gather on the occasion of his 85th birthday. By sheer coincidence, my talk will start in the East addressing a practical optimization problem under uncertainty where, as will be seen, there has not much been left for optimization but still something for planning. Both practical need and inner mathematical thirst for knowledge have mutually stimulated research in optimization under uncertainty, of which the talk will address its stochastic branch. Simple problems con?rm that only the presence of uncertainty makes them nontrivial, yet requires optimization at all. Stochastic programming problems that easily can be formulated have initialized substantial algorithmic innovation beyond the traditional convex models in continuous variables. This went hand in hand with practical paradigm changes, such as deregulation and unbundling, which will be illustrated at cases from the power and gas industries. Getting back to the interview where George Dantzig confirmed considering himself a mathematician and denied there is a difference between pure and applied mathematics, I will make an attempt to support this by pointing to fruitful interaction of stochastic programming not only with the mathematical disciplines forming its name but also with topics from algebra and analysis for which interaction might come as a surprise.


Since 1998, Rüdiger Schultz is a Full Professor for Discrete Mathematics and Optimization in the Department of Mathematics at the University of Duisburg-Essen, Germany. His doctoral and habilitation degrees in Mathematics he has received from the Humboldt University Berlin in 1985 and 1995. Dr. Schultz’ primary research interests are in optimization under uncertainty, discrete optimization, and in industrial applications of mathematical optimization. His research accomplishments include seminal work on structure, stability, and algorithmic treatment of stochastic programs, in particular of models involving integer variables, risk aversion, and, more recently, also PDE constraints. He has made contributions to real-life applications of mathematical optimization in the power, natural gas, and chemical processes industries. He has co-authored more than 100 scientific papers. Currently, Dr. Schultz is Editor-in-Chief of the journal Computational Management Science” and Area Editor Linear and Stochastic Optimization of Operations Research Letters”. He is serving as a member of the editorial boards of five further research journals in Applied Mathematics and Operations Research.