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.
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Linderoth, J., Wright, S. Decomposition Algorithms for Stochastic Programming on a Computational Grid. Computational Optimization and Applications 24, 207–250 (2003). https://doi.org/10.1023/A:1021858008222
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DOI: https://doi.org/10.1023/A:1021858008222