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A splitting method for stochastic programs

delete2006-02-01
delete4
PRE
AI
T
Teemu Pennanen *
M
Markku Kallio
DOI：10.1007/s10479-006-6171-1delete
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Abstract

Abstract

En 中文
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.
Keywords:
PROXIMAL POINT ALGORITHM
MONOTONE-OPERATORS

Journal

Annals of Operations Research cover
Annals of Operations Research
IF:
4.5
Papers:
8.0K
Citations:
2.1W

Organization

No organization information available