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Service time-probability distribution curve
A common example is that service times follow an exponential probability distribution i.e. y=e-x
Service channels - these refer to the number of service points and queues; If there is only one queue, but several service counters, the customer at the head of the queue will move to the first free counter when it becomes available. Where this system operates, there is a basic multiple channel or multi-channel system.
If there are several services counter each with its own queue, there is a more complex multiple channel or multichannel system.
Traffic intensity- this is the ratio of the average arrival rate to the average service rate. Unless a service rate is faster than the rate of new customers arriving in the queue the queue gets longer. An important assumption in queuing theory is that the traffic intensity must be less than one.
Transition probabilities These are the probabilities of moving from one state to another in the next time period. Usually they are written in the form of a probability matrix.
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I have 20pages preparing a system flowchart assignment
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