Chance-Constrained Programming: an Extension of Statistical Method.
Abstract
The current state of development of change-constrained programming, its problems and their relationships to statistical methods, particularly the theory of testing statistical hypotheses, is presented. Tied together are the representations in terms of non-Archimedian Hilbert extensions of the real field (which differs from the standard non-standard analysis fields), regularization of chance constraints, acceptance regions, and chance-constrained games. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 1971
- Accession Number
- AD0729245
Entities
People
- Abraham Charnes
- M. J. L. Kirby
- William W. Cooper
Organizations
- University of Texas at Austin