A splitting method for stochastic programs

Teemu Pennanen; Markku Kallio

doi:10.1007/s10479-006-6171-1

A splitting method for stochastic programs

Teemu Pennanen, Markku Kallio

Research output: Contribution to journal › Article › peer-review

4 Citations (Scopus)

Abstract

This paper derives a new splitting-based decomposition algorithm for convex stochastic programs. It combines certain attractive features of the progressive hedging algorithm of Rockafellar and Wets, the dynamic splitting algorithm of Salinger and Rockafellar and an algorithm of Korf. We give two derivations of our algorithm. The first one is very simple, and the second one yields a preconditioner that resulted in a considerable speed-up in our numerical tests.

Original language	English
Pages (from-to)	259-268
Number of pages	10
Journal	ANNALS OF OPERATIONS RESEARCH
Volume	142
Issue number	1
DOIs	https://doi.org/10.1007/s10479-006-6171-1
Publication status	Published - Feb 2006

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title = "A splitting method for stochastic programs",

abstract = "This paper derives a new splitting-based decomposition algorithm for convex stochastic programs. It combines certain attractive features of the progressive hedging algorithm of Rockafellar and Wets, the dynamic splitting algorithm of Salinger and Rockafellar and an algorithm of Korf. We give two derivations of our algorithm. The first one is very simple, and the second one yields a preconditioner that resulted in a considerable speed-up in our numerical tests.",

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AB - This paper derives a new splitting-based decomposition algorithm for convex stochastic programs. It combines certain attractive features of the progressive hedging algorithm of Rockafellar and Wets, the dynamic splitting algorithm of Salinger and Rockafellar and an algorithm of Korf. We give two derivations of our algorithm. The first one is very simple, and the second one yields a preconditioner that resulted in a considerable speed-up in our numerical tests.

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JO - ANNALS OF OPERATIONS RESEARCH

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A splitting method for stochastic programs

Abstract

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