Reference no: EM13749593
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
|
191
|
312
|
241
|
|
0.10
|
212
|
342
|
262
|
|
0.10
|
225
|
362
|
275
|
|
0.10
|
234
|
376
|
284
|
|
0.15
|
244
|
391
|
294
|
|
0.15
|
256
|
409
|
306
|
|
0.10
|
266
|
424
|
316
|
|
0.10
|
275
|
438
|
325
|
|
0.10
|
288
|
458
|
338
|
|
0.05
|
309
|
488
|
359
|
The unit revenues and costs are given in the table below.
|
Fruit
|
Unit Revenue
|
Unit Cost
|
|
Apple
|
$1.20
|
$0.75
|
|
Orange
|
$1.05
|
$0.60
|
|
Banana
|
$0.50
|
$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 one week (Sunday 3/1 through Saturday 3/7/2015) 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). For this assignment, assume all demand is actually met (that is, sales = demand) and there is no spoilage.
3. Build a table for tracking total revenues, costs, and profit for the week. 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 over the week)
• Total Goods Cost (also based on combined sales)
• Fixed Costs (assume the weekly cost for store space is $100 for each fruit display, so $300 total)
• Profit/Loss (total revenue minus total costs)
4. Create a data table to generate 100 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 100 simulation runs.
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