Question Set 1.
You are an inventory management consultant. You have been hired by Whole Foods to help optimize inventory management for their produce department. Your immediate task is building a Monte Carlo simulation for sales of apples, oranges, and bananas. The probabilities of daily demand levels are:
Probability
|
Apples
|
Oranges
|
Bananas
|
0.05
|
141
|
236
|
265
|
0.10
|
162
|
266
|
286
|
0.10
|
175
|
286
|
299
|
0.10
|
184
|
300
|
308
|
0.15
|
194
|
315
|
318
|
0.15
|
206
|
333
|
330
|
0.10
|
216
|
348
|
340
|
0.10
|
225
|
362
|
349
|
0.10
|
238
|
382
|
362
|
0.05
|
259
|
412
|
383
|
The unit revenues and costs are given in the table below.
Fruit
|
Unit Revenue
|
Unit Cost
|
Apple
|
$1.45
|
$0.90
|
Orange
|
$1.55
|
$1.10
|
Banana
|
$0.60
|
$0.25
|
1. Build a table for the cumulative probability distribution for demand. It should be set up for use with the VLOOKUP function, with the cumulative probabilities on the left.
2. Build a table for tracking sales over the dates Sunday 11/2 through Saturday 11/22 with separate columns for apples, oranges, and bananas. This will just be the randomized demand value for each fruit for each day (like in 10.1.2 from the lab exercise on Monte Carlo simulations). You can assume all demand is actually met (that is, sales = demand).
3. Build a table for tracking total revenues, costs, and profit for tracked sales. This table should use the information provided in your answer to 2., above. Your table should calculate values for:
- Total Revenue (based on the combined sales of all three fruits)
- Total Goods Cost (also based on combined sales)
- Fixed Costs (assume the weekly cost for store space is $200 for each fruit display, so $1800 total: 3 displays x 3 weeks x $200)
- Profit/Loss (total revenue minus total costs)
4. Create a data table to generate 50 runs of the simulation. As in previous assignments, this must be an actual data table structure to earn full credit. Calculate the average profit over the 50 simulation runs.