Finite master programs in regularized stochastic decomposition
type: Item
instance of: scholarly article
title: Finite master programs in regularized stochastic decomposition
zbMATH Open document ID: 0828.90097
DOI: 10.1007/BF01582219
author: Julia L. Higle
author: Suvrajeet Sen
published in: Mathematical Programming. Series A. Series B
publication date: 1995-01-05T00:00:00Z
review text: In a series of papers the authors have suggested a stochastic decomposition method for the approximate solution of stochastic linear programs with recourse. Since the approximate master program is a piecewise linear function, the algorithm leads to the growth of the master program's dimension without bounds. In this paper the authors suggest to add to the master program a quadratic regularizing term. Then the master program can be limited to a finite number of cuts (at most to \(n_1+ 3\) cuts, where \(n_1\) is the number of first stage decision variables), while ensuring accumulation at an optimal solution.
reviewed by: Riho Lepp
Mathematics Subject Classification ID: 90C15
zbMATH DE Number: 707409
zbMATH Keywords: regularization
zbMATH Keywords: stochastic decomposition
zbMATH Keywords: recourse
MaRDI profile type: Publication
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description: scientific article; zbMATH DE number 707409