Several emerging applications, such as “Analytics of Things" and “Integrative Analytics" call for a fusion of statistical learning (SL) and stochastic optimization (SO). The Learning Enabled Optimization paradigm fuses ...

Computational studies on two-stage stochastic programming problems indicate that aggregate models have better scale-up properties than disaggregate ones, though the threshold of breaking even may be high. In this paper we ...

This paper focuses on solving two-stage stochastic mixed integer programs (SMIPs) with general mixed integer decision variables in both stages. We develop a decomposition algorithm in which the first stage approximation ...

For electricity market participants trading in sequential markets with differences in price levels and riskexposure, coordinated bidding is highly relevant. We consider a Nordic power producer who engages inthe day-ahead ...

We develop a new modeling and exact solution method for stochastic programming problems thatinclude a joint probabilistic constraint in which the multi-row random technology matrix is discretely distributed. We binarize ...

We consider the solution of a system of stochastic generalized equations (SGE) where theunderlying functions are mathematical expectation of random set-valued mappings. SGE hasmany applications such as characterizing ...

Stochastic programs are usually formulated with probability distributions that are exogenously given. Modeling and solving problems withendogenous uncertainty, where decisions can influence the probabilities, has remained ...

We present new algorithms for the dynamic generation of scenario trees for multistagestochastic optimization. The different methods described are based on random vectors, whichare drawn from conditional distributions given ...

This paper considers model uncertainty for multistage stochastic programs. The data and information structure of the baseline model is a tree, on which the decision problem is defined. We consider ambiguity neighborhoods ...

We illustrate the solution of a mixed-integer stochastic nonlinear optimization problem in an application of power management. In this application, a coupled system consisting of a hydro power station and a wind farm is ...