This paper reviews a queuing model for multiple servers. The average queue length can be estimated
simply from raw data from questionnaires by using the collected number of customers waiting in a queue
each minute. We can compare this average with that of queuing model. Three different models are used
to estimate a queue length: a single-queue multi-server model, single-queue single-server and multiplequeue
multi-server model. In case of more than one queue (multiple queue), customers in any queue
switch to shorter queue (jockey behavior of queue). Therefore, there are no analytical solutions available
for multiple queues and hence queuing simulation is run to find the estimates for queue length and
waiting time.
The empirical analysis of queuing system of ICA supermarket is that they may not be very efficient in
terms of resources utilization. Queues form and customers wait even though servers may be idle much of
the time. The fault is not in the model or underlying assumptions. It is a direct consequence of the
variability of the arrival and service processes. If variability could be eliminated, system could be designed
economically so that there would be little or no waiting, and hence no need for queuing models.
With the increasing number of customers coming to ICA for shopping, either for usual grocery or for
some house wares, there is a trained employee serving at each service unit. Sales checkout service has
sufficient number of employees (servers) which is helpful during the peak hours of weekdays. Other than
these hours, there is a possibility of short Queues in a model and hence no need to open all checkouts
counters for each hour. Increasing more than sufficient number of servers may not be the solution to
increase the efficiency of the service by each service unit.
When servers are analyzed with one queue for two parallel servers, the results are estimated as per server
whereas when each server is analyzed with its individual queue, the results computed from simulation are
for each server individually.