Answer the following questions and submit as a word or PDF document in the drobo

Question

Answer the following questions and submit as a word or PDF document in the drobox.

Use the data below to answer #1 through 7.

Month

Sales

1

4324

2

4596

3

4571

4

3180

5

3514

6

2296

7

3913

8

4948

9

3102

10

2164

11

3720

12

3139

13

2548

14

2128

15

2692

1)      Using double exponential smoothing with an alpha () of 0.3 and a beta () of 0.7, create a forecast for month 16. (Use the linear regression of months 1 to 15 to determine the starting points for month 1.)

2)      What is the MAD of the above forecast (use months 4 through 15 to determine).

3)      What is the Forecast Bias of the above forecast (use months 4 through 15 to determine).

4)      Using double exponential smoothing with an alpha () of 0.6 and a beta () of 0.2, create a forecast for month 16. (Use the linear regression of months 1 to 15 to determine the starting points for month 1.)

5)      What is the MAD of the above forecast (use months 4 through 15 to determine).

6)      What is the Forecast Bias of the above forecast (use months 4 through 15 to determine).

7)      According to the MAD, which forecast is better (1 or 4)?

8)      A manager wants to know how many of each item to buy for next month to make the most profit. The three types of beverages he plans to buy materials for are milkshakes, root beer floats, and lemonade. He knows that he will sell everything that he orders. The milkshakes cost $0.90 to buy per serving. The root beer floats cost $0.80 each to buy. The lemonade cost $0.25 each serving to buy. They sell the milkshakes for $3.00, the root beer floats for $2.50 and the lemonade for $1.00 per serving.   He only has a budget of $1000 to drinks for next month. In addition, he wants to have at least as many milk shakes as root beer floats for the month. Create a linear programming model to help determine how many of each type of drink the manager should order. (Do not solve the problem; just formulate the linear programming model.)

Month

Sales

1

4324

2

4596

3

4571

4

3180

5

3514

6

2296

7

3913

8

4948

9

3102

10

2164

11

3720

12

3139

13

2548

14

2128

15

2692

Explanation / Answer

Answer of first four is given in attached tables

alpha= 0.6 beta= 0.2 month sale bt st abs(sale-st) bias 1 4324 272 4313.2 2 4596 273.296 4591.68 3 4571 238.0189 4688.59 4 3180 28.42577 3878.644 698.6437 698.6437 5 3514 -18.7426 3671.228 157.2278 157.2278 6 2296 -181.521 2838.594 542.5941 542.5941 7 3913 -30.8096 3410.629 502.3707 -502.371 8 4948 157.372 4320.728 627.2721 -627.272 9 3102 -7.75995 3652.44 550.44 550.44 10 2164 -185.442 2756.272 592.272 592.272 11 3720 -47.5412 3260.332 459.6678 -459.668 12 3139 -56.3961 3168.516 29.51639 29.51639 13 2548 -124.091 2773.648 225.6481 225.6481 14 2128 -186.677 2336.623 208.623 208.623 15 2692 -121.631 2475.178 216.8218 -216.822 2353.547 mad 400.9248

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