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NEW ESTIMATORS FOR EFFICIENT GI/G/1 SIMULATION

Published online by Cambridge University Press:  23 March 2005

Chia-Li Wang  and
Ronald W. Wolff
Chia-Li Wang
Affiliation:
Department of Applied Mathematics, National Dong Hwa University, Hualien, Taiwan, Republic of China, E-mail: cwang@mail.ndhu.edu.tw
Ronald W. Wolff
Affiliation:
Department of Industrial Engineering and Operations Research, University of California, Berkeley, California 94720, E-mail: wolff@ieor.berkeley.edu
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Abstract

For simulating GI/G/1 queues, we investigate estimators of stationary delay-in-queue moments that were suggested but not investigated in our recent article and we develop new ones that are even more efficient. Among them are direct spread estimators that are functions of a generated sequence of spread idle periods and are combinations of estimators. We also develop corresponding conditional estimators of equilibrium idle-period moments and delay moments. We show that conditional estimators are the most efficient; in fact, for Poisson arrivals, they are exact. In simulation runs with both Erlang and hyperexponential arrivals, conditional estimators of mean delay are more efficient than a published method that estimates idle-period moments by factors well over 100 and by factors of over 800 to several thousand for estimating stationary delay variance.

Information

Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 19 , Issue 2 , April 2005 , pp. 219 - 239
Copyright
© 2005 Cambridge University Press

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References

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