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Decomposition Algorithms for Stochastic Programming on a Computational Grid

Jeff Linderoth (jtl3***at***lehigh.edu)
Stephen Wright (swright***at***cs.wisc.edu)

Abstract: 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.

Keywords: stochastic programming, parallel algorithms

Category 1: Stochastic Programming

Category 2: Optimization Software and Modeling Systems (Parallel Algorithms )

Citation: Optimization Technical Report 02-07, Computer Sciences Department, University of Wisconsin-Madison

Download: [Postscript][PDF]

Entry Submitted: 04/17/2001
Entry Accepted: 04/17/2001
Entry Last Modified: 09/30/2002

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