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Perturbation Analysis

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Encyclopedia of Operations Research and Management Science

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Introduction

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.

Let l(θ) be a performance measure of interest with parameter (possibly vector) of interest θ, focusing on those systems where l(θ) cannot be easily obtained through analytical means and therefore must be estimated from sample...

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Author information

Authors and Affiliations

  1. Decision, Operations, and Information Technologies Department, Robert H. Smith S, University of Maryland, 4305 Van Munching Hall, College Park, MD, 20742, USA

    Michael C. Fu

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  1. Michael C. Fu
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Correspondence to Michael C. Fu .

Editor information

Editors and Affiliations

  1. Robert H. Smith School of Business, University of Maryland, College Park, MD, USA

    Saul I. Gass

  2. Robert H. Smith School of Business and Institute for Systems Research, University of Maryland, College Park, MD, USA

    Michael C. Fu

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Fu, M.C. (2013). Perturbation Analysis. In: Gass, S.I., Fu, M.C. (eds) Encyclopedia of Operations Research and Management Science. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-1153-7_748

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  • DOI: https://doi.org/10.1007/978-1-4419-1153-7_748

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  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4419-1137-7

  • Online ISBN: 978-1-4419-1153-7

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