A simulation technique for estimation in perturbed stochastic activity networks
Article Abstract:
We are concerned with what-if analysis in estimating the expected value and the distribution function of completion time in stochastic activity networks. Widely used Monte Carlo simulation models of stochastic networks are often subject to errors caused by the estimated parameter(s) of underlying input distribution function. "What-if" analysis is needed to establish confidence with respect to small changes in the parameters of the input distributions. However, traditional "what-if" analysis requires a separate simulation run for each input value. Recently, a method based on Likelihood Ratio (LR) for estimating performance function for several scenarios using a single-run extrapolation has been presented. In this paper, we experiment the use of this LR method in a network with exponential arc durations. We also consider the method with a nonlinear control random variate (NCRV) and compare it to crude Monte Carlo. The results show that the NCRV method induces variance reduction and is an effective filter to stabilize statistical variation of this single-run estimate. (Reprinted by permission of the publisher.)
Publication Name: SIMULATION
Subject: Engineering and manufacturing industries
ISSN: 0037-5497
Year: 1992
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Simultaneous estimation of several percentiles
Article Abstract:
In many simulation studies the performance of the modeled system is characterized only by mean values of the performance indices. However, the percentiles are more informative in summarizing the performance. Several simultaneous percentiles, presented for example in the form of the boxplot, provide the analyst with better understanding of the system's behaviour. The simultaneous estimation of several percentiles is a cumbersome task. The extended P(superscript 2)-algorithm proposed in this study significantly reduces the computation of the estimation. The algorithm simultaneously estimates several percentiles without storing and sorting the observations. Empirical validation studies indicate the algorithm can be used in simulation studies. (Reprinted with permission of the publisher.)
Publication Name: SIMULATION
Subject: Engineering and manufacturing industries
ISSN: 0037-5497
Year: 1987
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