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Reduction of a Discrete Event Simulation to a Markov Chain

Conference · · Proceedings of the 11th Conference on Winter Simulation
OSTI ID:5891892
An event-driven, time-based stochastic simulation model may be modified in a straightforward manner to satisfy the axioms of a discrete-state, continuous-time Markov chain. The method requires casting the probability distribution of each random variable representing a time interval of the process into the form of a series of exponentially distributed stages. An algorithm for this transformation was developed. The technique is demonstrated by means of a simple example of a computer system simulation. The Markov chain representation of the simulation can be solved numerically; this solution provides an independent verification of the logic of the simulation. 9 figures.
Research Organization:
Brookhaven National Lab., Upton, NY (USA); New York Univ., NY (USA). Courant Inst. of Mathematical Sciences; Sperry Univac, St. Paul, MN (USA)
Sponsoring Organization:
USDOE
DOE Contract Number:
EY-76-C-02-0016
OSTI ID:
5891892
Report Number(s):
BNL-26707; CONF-791207-2
Conference Information:
Journal Name: Proceedings of the 11th Conference on Winter Simulation Journal Volume: 2
Country of Publication:
United States
Language:
English

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