The purpose of this assignment is to continue our study of discrete event simulation by enhancing the bank teller simulation program you modified in assignment 2.
Part 1 - Single Q, Single Teller
The program, as you modified, only prints
the average wait time and the number of customers that left the bank.
You are to modify the program to print the following statistics as well
Run the program for a simulation time of 500 minutes for a single teller and a maximum service time of 5 minutes. Complete the following table.
- Maximum length of the queue
- Min/max/average customer service times
- Teller utilization expressed as a percentage (percent of time teller was busy for each teller)
- Min/max/average length of time each customer spends in the bank
- Number of customers that entered the bank
| Possibility of Customer Arrival | 10% | 20% | 30% | 40% |
| Max Q Length | ||||
| Min/Max/Avg Service Time | ||||
| Avg. Wait Time | ||||
| Teller Utilization | ||||
| Min/Max/Avg. Time in Bank | ||||
| Number customers that entered bank | ||||
| Number of customers that left bank |
Part 2 - One Queue per Teller, and
One Queue for all 3 Tellers
In part two you will study the effect of having
one queue for all tellers verses one queue for each teller. Modify the
program to have one queue for each teller. When a customer enters
the bank the customer should be placed in the shortest queue. Each
teller services customers only from the corresponding queue and not other
teller's queue.
Complete additional tables (like the one in part 1) for three tellers. One table for one queue per system.
Data for Three Tellers and One Queue Per Bank
| Possibility of Customer Arrival | 10% | 20% | 30% | 40% | 50% | 60% | 70% | 80% | 90% |
| Max Q Length | |||||||||
| Min/Max/Avg Service Time | |||||||||
| Avg. Wait Time | |||||||||
| Teller 1 Utilization | |||||||||
| Teller 2 Utilization | |||||||||
| Teller 3 Utilization | |||||||||
| Min/Max/Avg. Time in Bank | |||||||||
| Number customers that entered bank | |||||||||
| Number of customers that left bank |
Data for Three Tellers and Three Queues
| Possibility of Customer Arrival | 10% | 20% | 30% | 40% | 50% | 60% | 70% | 80% | 90% |
| Max Q Length Teller 1 | |||||||||
| Max Q Length Teller 2 | |||||||||
| Max Q Length Teller 3 | |||||||||
| Min/Max/Avg Service Time | |||||||||
| Avg. Wait Time | |||||||||
| Teller 1 Utilization | |||||||||
| Teller 2 Utilization | |||||||||
| Teller 3 Utilization | |||||||||
| Min/Max/Avg. Time in Bank | |||||||||
| Number customers that entered bank | |||||||||
| Number of customers that left bank |
Since there are three tellers the bank can handle many more customers than with one teller, hence the arrival rate can be much higher. Try varying the possibility of customer arrival up to 90%, keeping the simulation time of 500 minutes and customer processing time of 5 minutes constant. The system may become unstable (queue length and average wait time go up dramatically before you reach 90%). Plot, on one graph, two curves of average wait time Vs customer arrival percent for 3 tellers - one curve for one queue per teller and one curve for one queue for the entire bank.
Which configuration of the bank results in lower
average customer wait time?
Due March 22nd