Perturbation analysis (PA) is a sample path technique for analyzing changes in performance measures of stochastic systems due to changes in system parameters. In terms of stochastic simulation, which is the main setting for PA, the objective is to estimate sensitivities of the performance measures of interest with respect to system parameters, preferably without the need for additional simulation runs over what is required to estimate the system performance itself. The primary application is gradient estimation during the simulation of discrete-event systems, e.g., queueing and inventory systems. Besides their importance in sensitivity analysis, these gradient estimators are a critical component in gradient-based simulation optimization methods.
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