ON THE SOLUTION OF TWO-STAGE LINEAR PROGRAMS UNDER UNCERTAINTY. NOTES ON LINEAR PROGRAMMING AND EXTENSIONS. PART 55

Abstract

A possible method for compensating for uncertainty in linear- programming problems is to replace the random elements by expected values or by pessimistic estimates of these values, or to recast the problem into a two-stage program so that, in the second stage, one can compensate for inaccuracies in the first stage. The purpose of this analysis is to examine the last of these methods in detail. More precisely, it investigates the conditions under which the first-stage decisions are optimal. In addition, formulas for using various existing computational algorithms to obtain an optimal solution are given.

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Document Details

Document Type
Technical Report
Publication Date
Aug 10, 1961
Accession Number
AD0263219

Entities

People

  • Albert Madansky
  • George Bernard Dantzig

Organizations

  • RAND Corporation

Tags

Communities of Interest

  • Air Platforms
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Applied Mathematics
  • Computations
  • Computer Programming
  • Convex Programming
  • Convex Sets
  • Equations
  • Government Procurement
  • Inequalities
  • Linear Programming
  • Mathematics
  • Military Research
  • Operations Research
  • Simplex Method
  • Theorems
  • United States

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Operations Research