Bounding Separable Recourse Functions with Limited Distribution Information

Abstract

The recourse function in a stochastic program with recourse can be approximated by separable functions of the original random variables or linear transformations of them. The resulting bound them involves summing simple integrals. These integrals may themselves be difficult to compute or may require more information about the random variable than is available. In this paper, we show that a special class of function has an easily computable bound that achieves the best upper bound when only first and second moment constraints are available. Keywords: Integration; Stochastic programming; Moment problem; Duality; Approximation.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1990
Accession Number
ADA219504

Entities

People

  • John R. Birge
  • Jose H. Dula

Organizations

  • University of Michigan

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Applied Mathematics
  • Chebyshev Approximations
  • Computer Programming
  • Distribution Functions
  • Engineering
  • Gaussian Quadrature
  • Inequalities
  • Integrals
  • Intervals
  • Linear Programming
  • Mathematics
  • Michigan
  • Numerical Integration
  • Operations Research
  • Probability
  • Random Variables
  • Universities

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Approximation Theory.
  • Calculus or Mathematical Analysis