Accession Number:

AD0736874

Title:

Chance-Constrained Linear Programming with Distribution-Free Constraints

Descriptive Note:

Technical rept.

Corporate Author:

FLORIDA UNIV GAINESVILLE DEPT OF INDUSTRIAL AND SYSTEMS ENGINEERING

Personal Author(s):

Report Date:

1971-12-01

Pagination or Media Count:

67.0

Abstract:

The report is concerned with methods of approximating the chance- constrained set S x such thatPrA xor Bor alpha when the underlying distribution, F. of the random variate A, B is non-normal. The resulting sets are completely distribution-free in that no assumptions are made about the form of F. or any of its parameters. The concept employed is the distribution- free tolerance region. This is a sample based region containing 100 alpha percent of the population, at a confidence level, beta. The elements of the distribution-free sets satisfy the chance-constraint, PrAx or B or alpha with a confidence of at least beta. Furthermore, the sample size required to attain this level of confidence is readily available in tabular or graphical form. The superiority of the distribution-free approach over existing chance- constrained methods is demonstrated using simulated gamma variates.

Subject Categories:

  • Operations Research

Distribution Statement:

APPROVED FOR PUBLIC RELEASE