Our client has determined the need to modify software for modeling its stores using statistical data not previously available.Our initial contract is to modify a simulation allowing the client to vary arrival and purchase distributions.The results will allow the client to determine final store size, number of checkout lanes/sales personnel and other key features based on the statistical distributions.The software should be developed in a modular fashion to allow additions and modifications of features.Initial parameters the customer wishes to modify include random customer arrival rates using the exponential distribution, shopping time utilizing a step function, and the number of simultaneous users allowed in the store at the same time.They also wish to track how many customers are lost due to specific store restrictions.Eventually we will be expected to determine the total number of items purchased, the number of clients purchasing specific numbers of items, total time spent shopping, and the minimum/maximum/and average/expected number of customers served during the day. Use of generics in Ada (templates in Java/C++) is encouraged.You must use a contiguously allocated circular queue allocated in the system "stack" (not the heap) to track available (free) task (employees/customers) in the store.When a free task is assigned a new job/customer , it is removed from the circular queue.Store size will be the maximum number of free employees simultaneously allowed in the service queue.The task must be returned to the queue when a customer completes and re-used to for future customers!

The customer would like us to test the software using random customer arrival times.The time between arrivals is exponentially distributed at 10 minute intervals.Experience has shown the following purchasing distribution.For example, 2% of customers leave without purchasing anything.Thirty present percent of customers purchase 5 items.A customer purchasing 0 items is considered a "lost" customer.

Percent making purchase

Number items purchased

2%

0

28%

3

30%

5

29%

10

8%

7

3%

1

Customers currently requires 4.5 minutes per item purchased including checkout time.

Once you have the model working and validated, your initial task is to vary the average exponential arrival time to determine the maximum arrival rate a store can sustain without losing more that 10% of its customers in an 8 hour day.Customers left in the store at the end of 8 hours should be allowed to complete their shopping experience and be included in the final discussion of results.We are required to submit a report clearly indicating the maximum arrival distribution and number of customers lost.A table exhibiting the number of customers served at different values of the exponential distribution must be included in the report. It should contain sufficient statistical information from your simulation to validate your model and support your conclusions.The client is not entirely sure of their needs.Be aware we must remain flexible and willing to make modifications required by the client.Based on the data collected, recommend the best size store to support customers based on an exponential arrival rate of 10 minutes between customers.Management would be please if you determined the size of the store size required to support an exponentially distributed arrival rate of 7 customers per minute.You must justify your data driven decision.