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# Accession Number:

## ADA513136

# Title:

## On Sample Size Control in Sample Average Approximations for Solving Smooth Stochastic Programs

# Descriptive Note:

# Corporate Author:

## NAVAL POSTGRADUATE SCHOOL MONTEREY CA DEPT OF OPERATIONS RESEARCH

# Report Date:

## 2009-12-21

# Pagination or Media Count:

##
29.0

# Abstract:

## We consider smooth stochastic programs and develop a discrete-time optimal-control problem for adaptively selecting sample sizes in a class of algorithms based on sample average approximations SAA. The control problem aims to minimize the expected computational cost to obtain a near-optimal solution of a stochastic program and is solved approximately using dynamic programming. The optimal-control problem depends on unknown parameters such as rate of convergence, computational cost per iteration, and sampling error. Hence, we implement the approach within a receding-horizon framework where parameters are estimated and the optimal- control problem is solved repeatedly during the calculations of a SAA algorithm. The resulting sample-size selection policy consistently produces near-optimal solutions in short computing times as compared to other plausible policies in several numerical examples.

# Distribution Statement:

## APPROVED FOR PUBLIC RELEASE

#