Accession Number : AD0759295

Title :   Penalty Function Methods for Constrained Stochastic Approximation,

Corporate Author : BROWN UNIV PROVIDENCE R I DIV OF APPLIED MATHEMATICS

Personal Author(s) : Kushner,Harold J. ; Sanvicente,Emilio G.

Report Date : APR 1973

Pagination or Media Count : 21

Abstract : The paper is concerned with sequential Monte Carlo methods for optimizing a system under constraints. The authors wish to minimize f(x) where (q sub i) (x) 2 or = O, i = 1,...,m, must hold. The (q sub i) (x) can be calculated, but f(x) can only be observed in the presence of noise. A general approach, based on an adaptation of a version of stochastic approximation to the penalty function method, is discussed, and a convergence theorem proved. (Author Modified Abstract)

Descriptors :   (*STOCHASTIC PROCESSES, APPROXIMATION(MATHEMATICS)), MONTE CARLO METHOD, SEQUENTIAL ANALYSIS, SYSTEMS ENGINEERING, RANDOM VARIABLES, DISTRIBUTION FUNCTIONS, OPTIMIZATION

Subject Categories : Operations Research

Distribution Statement : APPROVED FOR PUBLIC RELEASE