1992 | OriginalPaper | Buchkapitel
Performance evaluation for the score function method in sensitivity analysis and stochastic optimization
verfasst von : Søren Asmussen, Reuven Rubinstein
Erschienen in: Simulation and Optimization
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Estimating systems performance ??(ρ) = ?? ρ L and the associated sensitivity (the gradient ∇??(ρ)) for several scenarios via simulation generally requires a separate simulation for each scenario. The score function (SF) method handles this problem by using a single simulation run, but little is known about how the estimators perform. Here we discuss the efficiency of the SF estimators in the setting of simple queueing models. In particular we consider heavy traffic (diffusion) approximations for the sensitivity and the variances of the associated simulation estimators, and discuss how to choose a ‘good’ reference system (if any) in order to obtain reasonably good SF estimators.