Accession Number : ADA186436

Title :   Sublinear Upper Bounds for Stochastic Programs with Recourse. Revision.

Descriptive Note : Technical rept.,

Corporate Author : MICHIGAN UNIV ANN ARBOR

Personal Author(s) : Birge, John R ; Wets, Roger J

PDF Url : ADA186436

Report Date : Jun 1987

Pagination or Media Count : 30

Abstract : Seperable sublinear functions are used to provide upper bounds on the recourse function of a stochastic program. The resulting problem's objective involves the inf-convolution of convex functions. A dual of this problem is formulated to obtain an implementable procedure to calculate the bound. Function evaluations for the resulting convex program only require a small number of single integrations in contrast with previous upper bounds that require a number of function evaluations that grows exponentially in the number of random variables. The sublinear bound can often be used when other suggested upper bounds are intractible. Computational results indicate that the sublinear approximation provides good, efficient bounds on the stochastic program objective value.

Descriptors :   *MATHEMATICAL PROGRAMMING, COMPUTATIONS, RANDOM VARIABLES, STOCHASTIC PROCESSES, TEST AND EVALUATION, NUMERICAL ANALYSIS, DISTRIBUTION FUNCTIONS, NORMAL DISTRIBUTION

Subject Categories : Operations Research

Distribution Statement : APPROVED FOR PUBLIC RELEASE