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dc.contributor.authorMorton, David P.
dc.contributor.authorWood, R. Kevin
dc.date.accessioned2014-01-22T19:08:23Z
dc.date.available2014-01-22T19:08:23Z
dc.date.issued1999
dc.identifier.urihttp://hdl.handle.net/10945/38423
dc.descriptionOperations Research, 47, pp. 943-956.en_US
dc.description.abstractWe consider the problem of bounding the expected value of a linear program (LP) containing random coeffecients, with applications to solving two-stage stochastic programs. An upper bound for minimizations is derived from a restriction of an equivalent, penalty-based formulation of the primal stochastic LP, and a lower bound is obtained from a restriction of a reformulation of the dual. Our "restricted recourse bounds" are more general and more easily computed than most other bounds because random coefficients may appear anywhere in the LP, neither independence nor boundedness of the coefficients is needed, and the bound is computed by solving a single LP or nonlinear program. Analytical examples demonstrate that the new bounds can be stronger than complementary Jensen bounds. (An upper bound is "complementary" to a lower bound, and vice versa). In computational work, we apply the bounds to a two-stage stochastic program for semiconductor manufacturing with uncertain demand and production rates.en_US
dc.rightsdefined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.subject.classificationProgramming, stochastic: bounds. Networks=graphs, stochastic. Facilities=equipment planning: capacity expansionen_US
dc.titleRestricted-Recourse Bounds for Stochastic Linear Programmingen_US
dc.typeArticleen_US
dc.contributor.departmentOperations Research (OR)


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