Distribution Free Methods for the Chance-Constrained Programming Model

Abstract

The paper is concerned with the development of certainty or deterministic equivalent nonlinear programming models from chance-constrained programming models. It contains a review of some of the historical developments in this area which were made by Charnes and Cooper, Kataoka, Miller and Wagner, Hillier, and Sengupta. The paper introduces a new, distribution free approach to chance-constrained programming which can be used with both single and joint chance constraints. Finally, the distribution free chance-constraned model is applied to the economic problem of input-output analysis.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1972
Accession Number
AD0741414

Entities

People

  • Jon R. Thomas

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Agricultural Economics
  • Air Force
  • Algorithms
  • Convex Programming
  • Distribution Functions
  • Economics
  • Estimators
  • Linear Programming
  • Nonlinear Programming
  • Normal Distribution
  • Operations Research
  • Probability
  • Probability Distributions
  • Random Variables
  • Simplex Method
  • Statistical Analysis
  • Steepest Descent Method

Readers

  • Operations Research