Speede Car Rentals is open 24 hours and has two classes of customers - 25% are prenium customers who are promised a waiting time of 5 minutes or less from then they enter or they receive a 15.00 discount on their rental. The others are regular customers who will wait as long as they have to wait. Customers arrive about 2 minutes apart (exponential) and move about 4 meters at 1 mile per hour to either prenium counter (1 agent) or regular counter (2 agents). All customers have a uniformely distributed service time of from 2 to 7 minutes. Each agent cost 55.00 per hours and each completed customer contribute 8.00 to income (minus any discount)
Modeling Consideration:
We will set 2 type of entities; Prenium Customers and Regular Customer. We will set-up a data table and a sequence table. Data Table will have customer type (key), Priority, Mix (25% to 75%), and WaitTime Tally Statistic. The Sequence Table will direct the entity to the their appropriate counter. The model is drawn to scale and the entity speed is set to 1 mile/hour
Scenario a Model
We will run a experiment with 50 repetitions of 10 days each (with 3 days warm-up period).
In this scenario where the agents are dedicated to each type of customers, we can see that the agent utilization time is abount 56% and that the maximum wait time for Prenium Customers abount 30 minutes, for regular customers we have agent utilization time of about 84% and maximum wait time of abount 42 minutes.
In our next scenario, we will not have dedicated counters but we will take Prenium customer waiting in line as a priority with the next available agent.
Scenario a Model
We will run an experiment with 50 repetitions of 10 days each (with 3 days warm-up period)
From the results of this experiment, we can see that for this model, the maximum prenium customer wait time is down to about 18 minutes and the agent utilization is now 75% percent.
Let us exmamin the other statistic to determine which model is better.
Total Net Income for model a is much larger for the 2nd model.