A new simulation is proposed to overcome several of the limitation of discrete event simulation. It is based on the combination of analytic queuing networks and analytic uncertainty modeling. The analytic queue techniques gives an approximate transient solution to the general inter arrival time and general service time single server queue. Analytic uncertainty analysis is based on the beta distribution. It provides the entire uncertainty probability distribution can be fit based on the minimum, mean, maximum, and estimate of the mean and standard deviation statistics. In a complex results calculation, all that is required is to keep track of these statistics as the calculation proceeds. At any point in a calculation, the probability distribution of the result can be derived by fitting a beta distribution based on the four statistics. When analytic queuing is combined with analytic uncertainty, modelling dynamics uncertainty analysis becomes feasible. The time varying uncertainty distribution in resulting measures of effectiveness can be calculated at any specified time or over nay user specified time interval. The new capability is not available in discrete event simulation.

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Date created

• 1994

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• Document

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• Processing documentation available at: https://wiki.albany.edu/display/SCA/Processing+Ingested+Digital+Files

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fe35db792b573af835d96e6eba4759cd

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System Dynamic Society Records

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• This collection is part of the University Archives