We consider quadratic stochastic programs with random recourse — a class of problems which is perceived to be computationally demanding. Instead of using mainstream scenario tree-based techniques, we reduce computational complexity by restricting the space of recourse decisions to those linear and quadratic in the observations, thereby obtaining an upper bound on the original problem. To estima...

Tod Morrison University of Colorado at Denver and Health Sciences Center 14.

A computational method is developed for solving time consistent distributionally robust multistage stochastic linear programs with discrete distribution. The structure of the uncertain parameters described by a scenario tree. At each node this tree, an ambiguity set defined conditional moment constraints to guarantee consistency. This employs idea nested Benders decomposition that incorporates ...

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