Stochastic dominance provides a rigorous method to compare uncertain prospects without imposing restrictive assumptions on investor risk preferences, thus offering an alternative to traditional ...

In this paper we study the problems of pricing and optimizing sidecar and collateralized reinsurance portfolios. The academic literature on sidecar portfolio optimization that takes into account the ...

Professor Ruszczynski’s interests are in the theory, numerical methods and applications of stochastic optimization. He is author of "Nonlinear Optimization", "Lectures on Stochastic programming", and ...

Course in stochastic optimization with an emphasis on formulating, solving, and approximating optimization models under uncertainty. Topics include: Models and applications: extensions of the linear ...

Research areas: Healthcare optimization under uncertainty, Large-scale optimization, stochastic programming, decomposition-based integer programming algorithms ...

A first introduction to probability and statistics. This course will provide background to understand and produce rigorous statistical analysis including estimation, confidence intervals, hypothesis ...

A global research team led by scientists from China’s Tianjin Renai College has developed a novel stochastic optimization technique for enhanced dispatching and operational efficiency in PV-powered ...