Decomposition Algorithms for Stochastic Programming on a Computational Grid

dc.creatorLinderoth, Jeff
dc.creatorWright, Stephen
dc.date2001-06-18
dc.date.accessioned2026-07-07T04:42:13Z
dc.date.available2026-07-07T04:42:13Z
dc.descriptionWe 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.
dc.description44 pages
dc.identifierhttps://arxiv.org/abs/math/0106151
dc.identifierhttp://arxiv.org/abs/math/0106151
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/61682
dc.subjectOptimization and Control
dc.subject90C15; 65K05
dc.titleDecomposition Algorithms for Stochastic Programming on a Computational Grid
dc.typetext

Files

Collections