Abstract
Performance measures for stochastic Discrete Event Systems (DES) often involve finite or infinite horizon expectations of measurable costs and benefits. In its broader sense, the term “sensitivity analysis” refers to the estimation of the impact of changes in expected performance upon changes of some of the input parameters. In the particular case where the expected performance is differentiable, sensitivity analysis deals with the estimation of gradients of the expected performance with respect to some parameter of interest, called the control variable.
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Vázquez-Abad, F.J. (2000). A Course on Sensitivity Analysis for Gradient Estimation of Des Performance Measures. In: Boel, R., Stremersch, G. (eds) Discrete Event Systems. The Springer International Series in Engineering and Computer Science, vol 569. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-4493-7_1
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DOI: https://doi.org/10.1007/978-1-4615-4493-7_1
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