Introduction
Perturbation analysis (PA) is a sample path technique for analyzing changes in the performance of stochastic systems due to changes in system parameters. In terms of stochastic simulation — the main setting for the application of PA — the objective is to estimate sensitivities of the performance measures of interest with respect to system parameters while obtaining estimates of performance itself, without the need for additional simulation runs. The primary application is gradient estimation during the simulation of discrete-event systems, for example, queueing and inventory systems. Besides their importance in sensitivity analysis, these gradient estimators are a critical component in gradient-based simulation optimization methods.
Let l(θ) be a performance measure of interest with parameter (possibly vector) of interest θ. We are interested in those systems where l(θ) cannot be easily obtained through analytical means and therefore must be estimated from sample paths,...
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Fu, M.C. (2001). Perturbation analysis . In: Gass, S.I., Harris, C.M. (eds) Encyclopedia of Operations Research and Management Science. Springer, New York, NY. https://doi.org/10.1007/1-4020-0611-X_748
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DOI: https://doi.org/10.1007/1-4020-0611-X_748
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