Chance-Constrained Programming: an Extension of Statistical Method.
TEXAS UNIV AUSTIN CENTER FOR CYBERNETIC STUDIES
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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
- Administration and Management
- Operations Research