Question: A fast - food delivery store / service accepts orders from customers continuously ( operating 2 4 / 7 ) with interarrival times following an

A fast-food delivery store/service accepts orders from customers continuously (operating 24/7) with interarrival times following an exponential distribution with a mean of 5.2(all times given are in minutes). When an order is placed, it is first analyzed and the proper food preparation is determined, a process whose service time follows a triangular distribution with parameters 3,5.5,7. The order is then sent to one of 3 cooking preparation servers (probability 0.95) or sent to a noncooking server (probability 0.05). The cooking preparation servers are servers who prepare food that needs to be cooked for the order, with service time following a triangular distribution with parameters 4,6,7.1. The non-cooking server deals with orders that do not require cooking (maybe the customer only ordered ice cream), and has a service time following a triangular distribution with parameters 3,8, and 12. After being prepared by either type of server, the food is then sent to be packed and prepared to delivery, a process with a service time following a triangular distribution with parameters 2,3, and 3.7. Then the packaged food leaves the system as it is sent to be delivered to the customer. The non-cooking server only handles 1 order at a time. The three cooking preparation servers can be considered as one station with a capacity of three (i.e., use one Server object to model all three cooking servers). Lets assume that movement time between stations is negligible. (i) Run a simulation of 14 round-the-clock 24-hour days for 50 replications and observe the average total time in system of orders, as well as the throughput of the fast-food store (number of orders that leave the center to be delivered over the 14 days).(ii) If you could afford to add resources, where is the need most pressing? Evaluate those scenarios and compare the results with that from the baseline model. (iii) Add appropriate animation to your model. Note: replication length is 14 days, i.e., each replication lasts for 14 days. You are asked to run the simulation model for 50 replications.

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