Statistical models use to evaluate waiting lines and their impact on flow rates and inventory levels.
A Queue model is used to approximate a real queueing situation or system, so the queueing behaviour can be analysed mathematically. Queueing models allow a number of useful steady state performance measures to be determined, including:
* the average number in the queue, or the system,
* the average time spent in the queue, or the system,
* the statistical distribution of those numbers or times,
* the probability the queue is full, or empty, and
* the probability of finding the system in a particular state.
These performance measures are important as issues or problems caused by queueing situations are often related to customer dissatisfaction with service or may be the root cause of economic losses in a business. Analysis of the relevant queueing models allows the cause of queueing issues to be identified and the impact of proposed changes to be assessed.
Queueing models are generally constructed to represent the steady state of a queueing system, that is, the typical, long run or average state of the system. As a consequence, these are stochastic models that represent the probability that a queueing system will be found in a particular configuration or state.