Regularized Decomposition of High-Dimensional Multistage Stochastic Programs with Markov Uncertainty

@article{Asamov2018RegularizedDO,
  title={Regularized Decomposition of High-Dimensional Multistage Stochastic Programs with Markov Uncertainty},
  author={Tsvetan Asamov and Warren B. Powell},
  journal={SIAM Journal on Optimization},
  year={2018},
  volume={28},
  pages={575-595}
}
We develop a quadratic regularization approach for the solution of high–dimensional multistage stochastic optimization problems characterized by a potentially large number of time periods/stages (e.g. hundreds), a high-dimensional resource state variable, and a Markov information process. The resulting algorithms are shown to converge to an optimal policy after a finite number of iterations under mild technical assumptions. Computational experiments are conducted using the setting of optimizing… CONTINUE READING

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