Decomposition algorithms for stochastic programming on a computational grid

Jeff Linderoth; Stephen Wright

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SPEPS Preprint

Author(s):	Jeff Linderoth, Argonne National Laboratory Stephen Wright, Argonne National Laboratory
Title:	Decomposition algorithms for stochastic programming on a computational grid
Date of Acceptance:	26.05.2001
Submission Date:	17.04.2001
Series Title:	Stochastic Programming E-Print Series (SPEPS)
Editors:	Julie L. Higle; Werner Römisch; Surrajeet Sen
Complete Preprint:	pdf (urn:nbn:de:kobv:11-10058173)
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Abstract (eng):

We describe algorithms for two-stage stochastic linear programming with recourse and their implementation on a grid computing platform. In particular, we examine serial and asynchronous versions of the L-shaped method and a trust-region method. The parallel platform of choice is the dynamic, heterogeneous, opportunistic platform provided by the Condor system. The algorithms are of master-worker type (with the workers being used to solve second-stage problems), and the MW runtime support library (which supports master- worker computations) is key to the implementation. Computational results are presented on large sample average approximations of problems from the literature.

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