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Scenario decomposition of risk-averse multistage stochastic programming problems

Ricardo A. Collado(collado***at***rutcor.rutgers.edu)
David Papp(dpapp***at***rutcor.rutgers.edu)
Andrzej Ruszczyński(rusz***at***business.rutgers.edu)

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 method is applied to a risk-averse inventory and assembly problem. In addition, we develop a partially regularized bundle method for nonsmooth optimization.

Keywords: dynamic measures of risk, duality, decomposition, bundle methods

Category 1: Stochastic Programming

Citation: RUTCOR, Rutgers University, Piscataway, NJ 08854

Download: [PDF]

Entry Submitted: 08/29/2010
Entry Accepted: 08/30/2010
Entry Last Modified: 08/29/2010

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