We develop a two-stage stochastic integer programming model for the simultaneous optimization of power production and day-ahead power trading. The model rests on mixed-integer linear formulations for the unit commitment ...

This paper derives a new splitting-based decomposition algorithm for convex stochastic programs. It combines certain attractive features of the progressive hedging algorithm of Rockafellar and Wets, the dynamic splitting ...

We consider integrated chance constraints (ICC), which provide quantitative alternatives for traditional chance constraints. We derive explicit polyhedral descriptions for the convex feasible sets induced by ICCs, for the ...

This paper discusses the allocation of capital over time with several risky assets. The capital growth log utility approach is used with conditions requiring that specific goals are achieved with high probability. The ...

We consider multiple simple recourse (MSR) models, both continuous and integer versions, which generalize the corresponding simple recourse (SR) models by allowing for a refined penalty cost structure for individual shortages ...

In this paper, we study alternative primal and dual formulations of multistage stochastic convex programs (SP). The alternative dual problems which can be traced to the alterna-tive primal representations, lead to stochastic ...

We propose the use of sequences of separable, piecewise linear approximations for solving classes of nondiffferential stochastic optimization problems. The approximations are estimated adaptively using a combination of ...

In this paper we present a branch-and-price method to solve special structured multi-stage stochastic integer programming problems. We validate our method on two different versions of a multi-stage stochastic batch-sizing ...