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 2.7, Problem 18P
Summary Introduction
To determine: The two step ahead prediction for July till December 2013 using a four month moving average.
Introduction:
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The following table shows the actual demand observed over the last 11 years:
Year
1
2
3
4
5
6
7
8
9
10
11
Demand
7
9
6
10
12
7
12
12
9
9
8
Part 2
Using exponential smoothing with
α =
0.30 and a forecast for year 1 of
6.0, provide the forecast from periods 2 through 12 (round your responses to one decimal place).
Part 3
Provide the forecast from periods 2 through 12 using the naive approach (enter your responses as whole numbers).
Month Demand
Forecast
Error
1
20
2
18
3
21
4
25
5
24
6
27
7
22
8
30
9
23
10
20
11
29
12
22
Mean
Abs Error
Problem 6: The demand manager of Maverick Jeans is responsible
for ensuring sufficient warehouse space for the finished jeans that
come from the production plants. It has occasionally been necessary
to rent public warehouse space, something that Maverick would like
to avoid. In order to estimate the space requirements the demand
manager is evaluating moving-average forecasts. The demand (in
1,000 case units) for the last fiscal year is shown below.
Bias
MAD
(mean
error)
Month 1 2 3 4 5 6 7 8 9 10 11 12
Demand 20 18 21 25 24 27 22 30 23 20 29 22
Use a three-month moving average to estimate the month-in-
advance forecast of demand for months 4-12. Calculate the Bias
and MAD. (Note: Adjust all cell values to two decimal points.)
National Standard, Inc. sells radio frequency identification (RFID) tags. Monthly demand for a seven-month period is reported below:
Sales (1000 units)
Forecast
Observation
Month
Yt
Ft
1
February
19
2
March
18
3
April
15
4
May
20
5
June
18
6
July
22
7
August
20
8
September
?
Use Excel to plot the data and forecast September sales using the following methods:
The naïve forecast
A three-month moving average
Exponential smoothing with a smoothing coefficient of α = 0.2, assuming a February forecast of 19
A 3-month weighted moving average, with weights 0.60, 0.3, and 0.1. With 0.6 applied to the most recent past.
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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