Production and Operations Analysis, Seventh Edition
7th Edition
ISBN: 9781478623069
Author: Steven Nahmias, Tava Lennon Olsen
Publisher: Waveland Press, Inc.
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Chapter 2.6, Problem 12P
a.
Summary Introduction
To determine: The one step ahead forecasts for periods 3 through 12.
Introduction:
b.
Summary Introduction
To determine:The forecast errors for the periods 3 through 12.
Introduction: Forecasting is the main function of predicting the future using the information available for decision making. It is a mechanism for planning decisions based on the predicted information.
c.
Summary Introduction
To determine: The MAD, MSE and MAPE for the forecast errors calculated for periods 3 through 12.
Introduction: Forecasting is the main function of predicting the future using the information available for decision making. It is a mechanism for planning decisions based on the predicted information.
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Students have asked these similar questions
The monthly market shares of General Electric Company for 12
consecutive months follow.
A. Construct a time series plot. What type of pattern exists in the
data?
B. Develop three-month and four-month moving averages for
this time series. Does the three-month or the four-month
moving average provide the better forecasts based on MSE?
Explain your reasoning.
C. Using your results in (B), compute MAD, MAPE, and
Tracking Signal (TS). Which method provides better forecast?
Explain your reasoning. Assume TS limit of ±4.
D. Apply exponential smoothing to the data. Compute MSE,
MAPE, MAD, and TS. Use a = 0.3. How does exponential
smoothing compare with four-month moving average?
Assume TS limit of ±4.
Month
1
2
3
4
5
6
7
8
9
10
11
12
Market
Shares
23.39
23.56
23.02
23.03
23.60
23.37
23.21
23.40
23.31
23.94
23.39
23.50
Emergency calls to Winter Park, Florida’s 911 system, for the past 24 weeks are as follows:
Compute the exponentially smoothed forecast of calls for each week. Assume an initial forecast of 50 calls in the first week and use = 0.1. What is the forecast for the 25th week?
Reforecast each period using = 0.6.
Here are the actual tabulated demands for an item for a nine-month period (January through September). Your supervisor wants to test two forecasting methods to see which method was better over this period.
MONTH
ACTUAL
January
120
February
145
March
146
April
171
May
154
June
182
July
138
August
135
September
146
a. Forecast April through September using a three-month moving average.
b. Use simple exponential smoothing with an alpha of 0.20 to estimate April through September, using the average of January through March as the initial forecast for April.
c-1. Calculate MAD for Three-month moving average and Exponential smoothing.
c-2. Use MAD to decide which method produced the better forecast over the six-month period.
Chapter 2 Solutions
Production and Operations Analysis, Seventh Edition
Ch. 2.4 - Prob. 1PCh. 2.4 - Prob. 2PCh. 2.4 - Prob. 3PCh. 2.4 - Prob. 4PCh. 2.4 - Prob. 5PCh. 2.4 - Prob. 6PCh. 2.4 - Prob. 7PCh. 2.4 - Prob. 8PCh. 2.4 - Prob. 9PCh. 2.6 - Prob. 10P
Ch. 2.6 - Prob. 11PCh. 2.6 - Prob. 12PCh. 2.6 - Prob. 13PCh. 2.6 - Prob. 14PCh. 2.6 - Prob. 15PCh. 2.7 - Prob. 16PCh. 2.7 - Prob. 17PCh. 2.7 - Prob. 18PCh. 2.7 - Prob. 19PCh. 2.7 - Prob. 20PCh. 2.7 - Prob. 21PCh. 2.7 - Prob. 22PCh. 2.7 - Prob. 23PCh. 2.7 - Prob. 24PCh. 2.7 - Prob. 25PCh. 2.7 - Prob. 26PCh. 2.7 - Prob. 27PCh. 2.8 - Prob. 28PCh. 2.8 - Prob. 29PCh. 2.8 - Prob. 30PCh. 2.8 - Prob. 31PCh. 2.8 - Prob. 32PCh. 2.9 - Prob. 33PCh. 2.9 - Prob. 34PCh. 2.9 - Prob. 35PCh. 2.9 - Prob. 36PCh. 2.9 - Prob. 37PCh. 2.10 - Prob. 38PCh. 2.10 - Prob. 42PCh. 2.10 - Prob. 43PCh. 2.10 - Prob. 44PCh. 2.10 - Prob. 45PCh. 2 - Prob. 47APCh. 2 - Prob. 48APCh. 2 - Prob. 49APCh. 2 - Prob. 50APCh. 2 - Prob. 51APCh. 2 - Prob. 52APCh. 2 - Prob. 53APCh. 2 - Prob. 54APCh. 2 - Prob. 55APCh. 2 - Prob. 56APCh. 2 - Prob. 57APCh. 2 - Prob. 58AP
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