Accelerating the regularized decomposition method for two stage stochastic linear problems

Ruszczynski A & Swietanowski A (1997). Accelerating the regularized decomposition method for two stage stochastic linear problems. European Journal of Operational Research 101 (2): 328-342. DOI:10.1016/S0377-2217(96)00401-8.

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Abstract

Practical improvements of the regularized decomposition algorithm for two stage stochastic problems are presented. They are associated with the primal simplex method for solving subproblems. A penalty formulation of the subproblems is used, which facilitates crash and warm starts, and allows more freedom when creating the model. The computational results are highly encouraging.

Item Type: Article
Uncontrolled Keywords: Stochastic programming; Decomposition; Non-smooth optimization
Research Programs: Risk, Modeling, Policy (RMP)
Bibliographic Reference: European Journal of Operational Research; 101:328-342 [1997]
Depositing User: IIASA Import
Date Deposited: 15 Jan 2016 02:08
Last Modified: 29 Sep 2016 11:23
URI: http://pure.iiasa.ac.at/5045

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