County Bank has already used analytical models to obtain steady-state measures of queueing behavior. However, it wonders whether these provide very realistic estimates of what occurs during a 2-hour...

County Bank has already used analytical models to obtain steady-state measures of queueing behavior. However, it wonders whether these provide very realistic estimates of what occurs during a 2-hour peak period at the bank. During this peak period, arrivals occur according to a Poisson process of 2 per minute, there are 6 tellers employed, and each service time has a mean length of 2.7 minutes. The standard deviation of service times is estimated at 1.5 minutes, and a histogram of historical service times has a shape much like the shape in Figure 14.22, so that a gamma distribution appears to be reasonable. What insights can the bank manager obtain from simulation?

Objective To simulate the bank’s queueing system for a two-hour peak period so that we can compare its actual behavior to the steady-state behavior predicted by M/M/s and G/G/s analytical models.