The City bank executives are confronted with the problem of hiring optimal number of tellers. They need to hire enough cashiers so that clients don't have to stay too long on line. However, they do not want to employ too many cashiers because they want to save resources and maintain their clients. They need to employ an optimal number of tellers. The bank executives can do this through writing a program to simulate a bank. To do this, they must know the estimated times when customers arrive and how long their dealings take and write a simulator that arbitrarily generates people coming into a bank doing transactions, and see how the number of cashiers influences how long people wait, and how long tellers stay idle.
There are two tellers at the Citibank bank’s branch and a sample of four customers was observed. The table below shows customers’ arrival and service times for simulation.
- Person 1 enters bank at 1.5 minutes. The two tellers are idle, teller 1 started working on the first person's transaction. It took 5.7 minutes, so it was done at 7.2 minutes.
- At 2.8 minutes, person 2 entered the bank. The second teller is free, so he starts serving the customer. He took 1.9 minutes, so he was done at 4.7 minutes.
- At 3.3, person 3 entered the bank. Since the tellers were busy, so person 2 had to wait in line until one of the tellers was idle.
- At 4.7 minutes, second teller was free, the customer could now leave the queue and the teller could serve him. Third customer’s transaction took 8.7 minutes; it was over at 13.4 minutes.
- At 7.2 minutes, first teller is free. Since no one is in line, he remains idle.
- At 9.2 minutes, fourth person enters the bank. The first teller is free, so he started working on the customer's transaction. The transaction took 2.7 minutes, so it was done at 11.90.
- At 11.9, first teller was idle.
- At 13.4, second teller was idle.
The link: http://web.eecs.utk.edu/~parker/Courses/CS302-Fall06/Labs/Lab6/index.html
Albright, S. C., Zappe, C. J., Winston, W. L., & Broadie, M. N. (2011). Data analysis, optimization, and simulation modeling. Australia: South-Western Cengage Learning.
Guerrero, H. (2010). Excel data analysis: Modeling and simulation. Heidelberg: Springer.
Scheuermann, P. (1976). A simulation model for data base systems.