Q1. Weekly demand figures at Hot Pizza are as follows: (20 points) Week 102 114

Question

Q1. Weekly demand figures at Hot Pizza are as follows: (20 points) Week 102 114 118 100 98 119 98 102 102 92 98 10 12 a) b) c) d) Estimate demand for week 13 using a 3-week moving average (5 points) Estimate demand for week13 using a simple exponential smoothing with :0.4. (5 points) Evaluate the MAD, MAPE and MSE for two methods. (5 points) Which of the two methods do you prefer? Why? (5 points) Q2. Amazon sells 6,000 Lenovo PCs every month. Each PC costs $300 and Amazon has a holding cost of 20 percent (10 points) a) b) For what fixed cost per order would an order size of 1,200 units be optimal? (5 points) For what fixed cost per order would an order size of 600 units be optimal? (5 points) Q3. A North Face retail store in Chicago sells 500 jackets each month. Each jacket costs the store $100 and the company has an annual holding cost of 20 percent. The fixed cost of a replenishment order (including transportation) is $200. The store currently places a replenishment order every month for 500 jackets(20 points) a) b) What is the annual holding and ordering cost of the current replenishment policy? (10 points) If the retail store wants to minimize ordering and holding cost, what order size do you recommend? (5 How much would the optimal order reduce holding and ordering cost relative to the current replenishment policy? (5 points) c)

Explanation / Answer

As per policy only first question will be answered

1a ) taking the average of actuals of last three weeks i.e. average (week 10, week 11, week 12) , we get forecast for week 13 as 97

1b) we assume the forecast of week 1 as the same as actual. then calculate the forecast of subsequent weeks using the formulat

Forecast for this week = Forecast of last week + 0.4 ( Actual of last week - forecast of last week)

So, the forecasted demand comes out to be 99 for week 13

1 c) Absolute error = absoute of (actuals-forecast)

For moving average method. MAD = Average of absoute errors = 6.1

MSE = Average of square of errors = 64.4

MAPE = (total of absoulte errors )/ total forecast = 73.3/1289 = 6%

For second method (exponential smoothening)

For exponential smoothening method. MAD = Average of absoute errors = 8.5

MSE = Average of square of errors = 94.2

MAPE = (total of absoulte errors )/ total forecast = 101.6/1262 = 8%

d) out of the two methods, moving average method has lesser MAD and MAPE and hence it is more effective and preferable

Actuals Forecast
Using exponential
smoothing 1 102 102 2 114 102 3 118 107 4 100 111 5 98 107 6 119 103 7 98 110 8 102 105 9 112 104 10 102 107 11 92 105 12 98 100 13 99

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