The Chance-Constrained Critical Path for a Large Class of Distributions

Abstract

M. Kress proved for a special class of Location-Scale probability distributions there always exists a probability level for which the Chance Constrained Critical Path (CCCP) remains unchanged for all probabilities greater than or equal to that value. His chance constrained problem has zero-order decision rules and individual chance constraints. This paper extends his results to most of the common probability distributions. Keywords: Chance constrained programming.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1988
Accession Number
ADA196055

Entities

People

  • Abraham Charnes
  • L. Gong

Organizations

  • University of Texas at Austin

Tags

DTIC Thesaurus Topics

  • Business Administration
  • Distribution Functions
  • Intervals
  • Probability
  • Probability Distributions
  • Random Variables
  • Universities

Fields of Study

  • Mathematics

Readers

  • Operations Research
  • Statistical inference.