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Simulating Stable Stochastic Systems, II: Markov Chains
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Volume 21 ,  Issue 1  (January 1974) table of contents
Pages: 114 - 123  
Year of Publication: 1974
ISSN:0004-5411
Authors
Michael A. Crane  Control Analysis Corporation, 800 Welch Rd., Palo Alto, California
Donald L. Iglehart  Department of Operations Reserach, Stanford University, Stanford, California
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 3,   Downloads (12 Months): 32,   Citation Count: 29
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ABSTRACT

A technique for simulating GI/G/s queues is shown to apply to simulations of discrete and continuous-time Markov chains. It is possible to address questions of simulation run duration and of starting and stopping simulations because of the existence of a random grouping of observations which produces independent identically distributed blocks from the start of the simulation. This grouping allows confidence intervals to be obtained for a general function of the steady-state distribution of the Markov chain. The technique is illustrated with simulation of an (s, S) inventory model in discrete time and the classical repairman problem in continuous time. Consideration is also given to determining system sensitivity to errors and uncertainty in the input parameters.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
CHUNG, K.L. Markov Chaius with Stationary Transition Probabilities. Springer, Berlin, 1960.
 
2
CuuNa, K. L. A Course in Probability. Harcourt, Brace and World, New York, 1968.
3
 
4
FISRMAN, G., AND K~WA% P. The analysis of simulation generated time series. Management Sci. 13 (1967), 525-557.
 
5
WAGN~a, H. Principles of Operations Research. Prentice-Hall, Englewood Cliffs, N. J., 1969.

CITED BY  29
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Collaborative Colleagues:
Michael A. Crane: colleagues
Donald L. Iglehart: colleagues

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