# MGT-455 Module 3 Chapter 4 Problem Set - 4.1, 4.3, 4.5, 4.25, and 4.27

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MGT-455 Module 3 Chapter 4 Problem Set - 4.1, 4.3, 4.5, 4.25, and 4.27

Production/Operations Management - Forecasting

Grand Canyon University

Complete problems 4.1, 4.3, 4.5, 4.25, and 4.27 in the textbook.

Textbook: Operations Management (11th Edition)

Question 4.1:

The following gives the number of pints of type B blood used at Woodlawn Hospital in the past 6 weeks:

Weekof           Pints Used

31-08-14         360

07-09-14         389

14-09-14         410

21-09-14         381

28-09-14         368

05-10-14         374

a) Forecast the demand for the week of October 12 using a 3-week moving average.

b) Use a 3-week weighted moving average, with weights of .1, .3, and .6, using .6 for the most recent week. Forecast demand for the week of October 12.

c) Compute the forecast for the week of October 12 using exponential smoothing with a forecast for August 31 of 360 and an a of .2.

Question 4.3:

Refer to Problem 4.2. Develop a forecast for years 2 through 12 using exponential smoothing with a = .4 and a forecast for year 1 of 6. Plot your new forecast on a graph with the actual data and the naive forecast. Based on a visual inspection, which forecast is better?

Question 4.5:

The Carbondale Hospital is considering the purchase of a new ambulance. The decision will rest partly on the anticipated mileage to be driven next year. The miles driven during the past 5 years are as follows:

Year          Mileage

1               3,000

2               4,000

3               3,400

4               3,800

5               3,700

a) Forecast the mileage for next year (6th year) using a 2-year moving average.

b) Find the MAD based on the 2-year moving average. (Hint: You will have only 3 years of matched data.).

c) Use a weighted 2-year moving average with weights of .4 and .6 to forecast next year’s mileage. (The weight of .6 is for the most recent year.). What MAD results from using this approach to forecasting? (Hint: You will have only 3 years of matched data.)

d) Compute the forecast for year 6 using exponential smoothing, an initial forecast for year 1 of 3,000 miles, and a = .5.

Question 4.25:

The following gives the number of accidents that occurred on Florida State Highway 101 during the past 4 months:

MONTH           NUMBER OF ACCIDENTS

January          30

February        40

April              60

March            90

Forecast the number of accidents that will occur in May, using least-squares regression to derive a trend equation.

Question 4.27

George Kyparisis owns a company that manufactures sailboats. Actual demand for George’s sailboats during each of the past four seasons was as follows:

YEAR

SEASON        1        2       3       4

Winter       1400  1200  1000  900

Spring        1500  1400 1600 1500

Summer     1000  2100 2000 1900

Fall            600    750   650   500

George has forecasted that annual demand for his sailboats in year 5 will equal 5,600 sailboats.

Based on this data and the multiplicative seasonal model, what will the demand level be for George’s sailboats in the spring of year 5?

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