Abstract
For a risk-averse multistage stochastic optimization problem with a finite scenario tree, we introduce a new scenario decomposition method and we prove its convergence. The main idea of the method is to construct a family of risk-neutral approximations of the problem. The method is applied to a risk-averse inventory and assembly problem. In addition, we develop a partially regularized bundle method for nonsmooth optimization.
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This paper is dedicated to András Prékopa on the occasion of his 80th birthday.
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Collado, R.A., Papp, D. & Ruszczyński, A. Scenario decomposition of risk-averse multistage stochastic programming problems. Ann Oper Res 200, 147–170 (2012). https://doi.org/10.1007/s10479-011-0935-y
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DOI: https://doi.org/10.1007/s10479-011-0935-y