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Performance measures for single server systems | 12/10 Session Links |
As you can see, the convention in these formulas is to use Greek letters to represent some of the parameters of this model. If you’re unfamiliar with the Greek alphabet, this can be a little challenging, but not to worry, there are only three symbols in use here. The Greek letters we use are λ (called “lambda”), for the mean arrival rate; μ (called “mu”), for the mean service rate; and ρ (called “rho”), which is the ratio λ/μ.
By the way, if the mean service rate is less than the mean arrival rate, then customers are arriving faster than they can be serviced, and the queue grows indefinitely. In that situation, the system is not at equilibrium. Thus, since we assume that the system is at equilibrium, we know that the mean service rate is greater then the mean arrival rate, for all systems to which this model applies. That is, ρ < 1.
Last Modified: Wednesday, 27-Apr-2016 04:15:26 EDT
Modeling service systems in general is extraordinarily complex, but as we’ve seen, if we make reasonable approximations, we can gain powerful tools that are very easy to apply. In the case of service systems, we assumed that the system was at equilibrium or close to it. Analogously, we can make simplifying assumptions for many other complex questions. Examples are process control, resource scheduling, resource allocation, cost allocation, vehicle routing, and many more.