We investigate risk-averse stochastic optimization problems with a risk-shaping constraint in the form of a stochastic-order relation. Both univariate and multivariate orders are considered. We extend ...

We consider stochastic mathematical programs with complementarity constraints in which both the objective and constraints involve limit functions that need to be approximated. Such programs can be ...

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 ...

Researchers examined problems related to the timing and scheduling of surgeries and patients' stays in recovery units. In ...

Stochastic Sauna is a traditional workshop that brings together researchers and students working on probability, statistics, and their applications. The 2022 occasion will be held on 20th December ...

Scientists have developed a new optimization approach that combines both day-ahead optimization and real-time optimization to improve operations of PV-driven EV charging stations. The framework is ...

One of the interesting changes in terminology is that of the meaning of machine learning (ML). In the olden days, way back in the 1980s, machine learning referred almost exclusively to the to ...