Production and Operations Analysis, Seventh Edition
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 24P

a.

Summary Introduction

To calculate:The observed weekly sales of ball peen hammers at one of the town hardware shop over an eight week period have been 14, 9, 30, 22, 34, 12, 19, and 23. To get the solution of the one step ahead forecast for weeks through 8.

Introduction:The current forecast is the weighted average of the last forecast and the current value of demand

  Ft=αDt1+(1α)Ft1where0α

a.

Expert Solution
Check Mark

Answer to Problem 24P

The one step ahead forecast from week 4 to week 8 are F4=17.67, F5= 20.33, F6= 28.67, F7= 22.67, F8= 21.67

Explanation of Solution

Four month average of one step ahead forecast from week 4 to week 8 is calculated below:

    WeekDemandMAD
    114
    29
    330
    42217.67
    53420.33
    61228.67
    71922.67
    82321.67

Therefore, one step ahead forecast from week 4 to week 8 are F4=17.67, F5= 20.33, F6= 28.67, F7= 22.67, F8= 21.67.

b.

Summary Introduction

To calculate:The exponential smoothing forecasts for weeks 4 through 8.

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.

b.

Expert Solution
Check Mark

Answer to Problem 24P

    WeekDemandMADExponential Smoothing|Error|MAD   |Error|
    114
    29
    330
    42217.6717.674.334.33
    53420.3318.3215.6813.67
    61228.6720.678.6716.67
    71922.6719.370.373.67
    82321.6719.313.691.33
    Total32.7439.67

Explanation of Solution

The exponential smoothing forecasts for weeks 4 through 8 are calculated below:

  Ft=αDt+(1α)Ft1F4=17.67F5=(0.15)(22)+(0.85)(17.67)=18.32F6=(0.15)(34)+(0.85)(18.32)=20.67F7=(0.15)(12)+(0.85)(20.67)=19.37

  F8=(0.15)(19)+(0.85)(19.37)=19.32

c.

Summary Introduction

To calculate: Based on the MAD, to find out the method which did better.

Introduction: Forecasting error can be evaluated using the following formula:

  MAD=1ni=1n|ei|

c.

Expert Solution
Check Mark

Answer to Problem 24P

  MAD=1539.67=7.93

Explanation of Solution

MAD for Smoothing constant, α = 0.15

  MAD=1539.67=7.93

So, the exponential smoothing method is better than moving average method for the five weeks.

d.

Summary Introduction

To calculate: The exponential smoothing forecast made at the end of week 6 for the sales in week 12.

Introduction: Forecasting error can be evaluated using the following formula:

  MAD=1ni=1n|ei|

d.

Expert Solution
Check Mark

Answer to Problem 24P

The forecast made through exponential smoothing is in week 6 for sales in week 12 is 20.67.

Explanation of Solution

The exponential smoothing constant forecast made in the week 6 is the same for the demand in week 7 for sales of in week 12. Therefore, the forecast made through exponential smoothing in week 6 for sales in week 12 is 20.67.

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Students have asked these similar questions
) Consider the following time series data: Week 1     2    3   4    5    6 Value 18  13  16  11 17 14 i)Construct a time series plot. What type of pattern exist in the data? ii)Develop a three – week moving average for the time series. Compute MSE and a forecast cast for week 7. Use alpha = 0.2 to compute the exponential smoothing value for the time series. Compute MSE and a forecast for week 7. IV)Compare the three -week moving average forecast with exponential smoothing forecast using alpha = 0.2. Which appears to provide the better forecast based on MSE? Explain V)Use trial and error to find a value of the exponential smoothing. Coefficient Alpha that result in a smaller MSE than what you calculated for alpha = 0.2.
6) 4 Consider the following time series data.    Month  1     2     3      4         5          6         7   Value    24   13   20    12      19        23      15 i) Construct a time series plot. What type of pattern exist in the data? ii)Develop a three – week moving average for the time series. Compute MSE and a forecast cast for week 8. iii)Use alpha = 0.2 to compute the exponential smoothing value for the time series. Compute MSE and a forecast for week 8. iv)Compare the three -week moving average forecast with exponential smoothing forecast using alpha = 0.2. Which appears to provide the better forecast based on MSE? Explain v)Use trial and error to find a value of the exponential smoothing. Coefficient Alpha that result in a smaller MSE than what you calculated for alpha = 0.2.
The demand (in number of units) for Apple iPad over the past 6 months at BestBuy is summarized below. Month Nov 2019 Dec 2019 Demand 45 48 Jan 2020 50 Feb 2020 Mar 2020 Apr 2020 42 46 51 Consider the following three forecasting methods: • Two-month weighted moving average, with weights 6 and 2 (more weight assigned to more recent data) Exponential smoothing with a = 0.7. Let the initial forecast for Nov 2019 be 46. • A trend line projection in the form ŷ = a+bx . To simplify computations, transform the value of x (time) to simpler numbers – designate Nov 2019 as x=1, Dec 2019 as x= 2, etc. (a ) For each of the above methods, forecast the demand of Apple iPad for May 2020. (b) Consider only the two-month weighted moving average method, compute the MAD measure and the MSE measure using the data from Jan 2020. (c) Use the trend line to forecast the demand of Apple iPad for Dec 2020. Give your opinion regarding the reliability of the forecast.
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