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Truncation rules in simulation analysis : effect of batch size, time scale and input distribution on the application of Schriber's rule

The objective of many simulations is to study the
steady-state behavior of a nonterminating system. The
initial conditions of the system are often atypical because
of the complexity of the system. Simulators often start
the simulation with the system empty and idle, and
truncate, or delete, some quantity of the initial
observations to reduce the initialization bias.
This paper studies the application of Schriber's
truncation rule to a queueing model, and the effects of
parameter selection. Schriber's rule requires the
simulator to select the parameters of batch size, number of
batches, and a measure of precision. In addition,
Schriber's rule assumes the output is a time series of
discrete observations. Previous studies of Schriber's rule
have not considered the effect of variation in the time
scale (time between observations).
The performance measures for comparison are the mean
squared error and the half-length of the confidence
interval. The results indicate that the time scale and
batch size are significant parameters, and that the number
of batches has little effect on the output. A change in
the distribution of service time did not alter the results.
In addition, it was determined that multiple replicates
should be used in establishing the truncation point instead
of a single run, and the simulator should carefully
consider the choice of time scale for the output series and
the batch size. / Graduation date: 1991
Date04 June 1990
CreatorsBaxter, Lori K.
ContributorsRandhawa, Sabah U.
Source SetsOregon State University
Detected LanguageEnglish

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