Article ID: | iaor19951943 |
Country: | United States |
Volume: | 40 |
Issue: | 11 |
Start Page Number: | 1562 |
End Page Number: | 1578 |
Publication Date: | Nov 1994 |
Journal: | Management Science |
Authors: | Glynn Peter W., LEcuyer Pierre |
Keywords: | gradient methods, queues: theory, stochastic processes |
Approaches like finite differences with common random numbers, infinitesimal perturbation analysis, and the likelihood ratio method have drawn a great deal of attention recently as ways of estimating the gradient of a performance measure with respect to continuous parameters in a dynamic stochastic system. In this paper, the authors study the use of such estimators in stochastic approximation algorithms, to perform so-called ‘single-run optimizations’ of steady-state systems. Under mild conditions, for an objective function that involves the mean system time in a