Title :
Sensitivity Analysis for Robust Design Experiments
Author_Institution :
IRISA-INRIA, Rennes
Abstract :
We analyze the computation of sensitivities in network reliability analysis. The associated models are graphs whose components are weighted by probabilities (their reliabilities) and they are widely used, for instance, in the design of communication networks. The paper deals with the sensitivities of usual reliability network metrics, with respect to the reliabilities of the components. The importance of sensitivities in this context is discussed and it is shown how to efficiently estimate the vector of sensitivities using Monte Carlo procedures. A first result allows to evaluate sensitivities using the standard Monte Carlo approach. A second method is then presented to deal efficiently with the rare event case. The ideas presented here can be applied to other classes of reliability problems and/or methods
Keywords :
Monte Carlo methods; graph theory; sensitivity analysis; telecommunication network reliability; Monte Carlo method; communication network; network reliability analysis; reliability network metrics; reliability problem; sensitivity analysis; 1f noise; Multi-stage noise shaping; Noise level; Noise measurement; Noise robustness; Predictive models; Product design; Robust control; Sensitivity analysis; Working environment noise;
Conference_Titel :
Simulation Conference, 2005 Proceedings of the Winter
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-9519-0
DOI :
10.1109/WSC.2005.1574483