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Convergence of perturbation analysis estimates for discontinuous sample functions: a general approach

Published online by Cambridge University Press:  01 July 2016

Reuven Y. Rubinstein  and
Ferenc Szidarovszky
Reuven Y. Rubinstein
Affiliation:
Harvard University
Ferenc Szidarovszky*
Affiliation:
The University of Arizona
*
∗∗Postal address: Systems and Industrial Engineering Department, The University of Arizona, Tucson, AZ 85721, USA.
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Abstract

Generalized perturbation analysis (PA) estimates to study sensitivity of performance measures of discrete events dynamic systems for discontinuous sample functions are introduced. Their convergence conditions and rate of convergence are given. It is shown that the PA estimates based on a single sample path always converge faster to the unknown sensitivity parameter (vector of parameters) than their counterpart—crude Monte Carlo ones.

Keywords

QUEUEING NETWORKSMONTE CARLO METHODSENSITIVITY ANALYSISSIMULATION
Type
Research Article
Information
Advances in Applied Probability , Volume 20 , Issue 1 , March 1988 , pp. 59 - 78
Copyright
Copyright © Applied Probability Trust 1988 

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Footnotes

∗

Present address: Technion, Faculty of Industrial Engineering, Haifa, 32000 Israel.

Research supported in part by the U.S. Office of Naval Research Contract under N00014-79-C-0776, National Science Foundation Grant ECS82-13680, and a grant from C.S. Draper Laboratories.

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