Practical Management Science
6th Edition
ISBN: 9781337406659
Author: WINSTON, Wayne L.
Publisher: Cengage,
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Textbook Question
Chapter 10.4, Problem 12P
In August of the current year, a car dealer is trying to determine how many cars of the next model year to order. Each car ordered in August costs $20,000. The demand for the dealer’s next year models has the probability distribution shown in the file P10_12.xlsx. Each car sells for $25,000. If demand for next year’s cars exceeds the number of cars ordered in August, the dealer must reorder at a cost of $22,000 per car. Excess cars can be disposed of at $17,000 per car. Use simulation to determine how many cars to order in August. For your optimal order quantity, find a 95% confidence interval for the expected profit.
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Scenario
You have been given a task to create a demand forecast for the second year of sales of a premium outdoor grill.
Accurate forecasts are important for many reasons, including for the company to ensure they have the materials
they need to create the products required in a certain period of time. Your objective is to minimize the forecast
error, which will be measured using the Mean Absolute Percentage Error (MAPE) with a goal of being below 25%.
You have historical monthly sales data for the past year and access to software that provides forecasts based on
five different forecasting techniques (Naïve, 3-Month Moving Average, Exponential Smoothing for .2, Exponential
Smooth for .5, and Seasonal) to help determine the best forecast for that particular month. Based on the given
data, you will identify trends and patterns to create a more accurate forecast.
Approach
Consider the previous month's forecast to identify which technique is most effective. Use that to forecast the next…
Approach
Consider the previous month's forecast to identify which technique is most effective. Use that to forecast the next
month.
Remember to select the forecasting technique that produces the forecast error nearest to zero. For example:
a. Naïve Forecast is 230 and the Forecast Error is -15.
b. 3-Month Moving Forecast is 290 and the Forecast Error is -75.
c. Exponential Smoothing Forecast for .2 is 308 and the Forecast Error is -93.
d. Exponential Smoothing Forecast for .5 is 279 and the Forecast Error is -64.
e. Seasonal Forecast is 297 and the Forecast Error is -82.
The forecast for the next month would be 230 as the Naïve Forecast had the Forecast Error closest to zero with a
-15. This forecasting technique was the best performing technique for that month. You do not need to do any
external analysis-the forecast error for each strategy is already calculated for you in the tables below.
Naïve
Month Period
Actual
Demand
Naïve Forecast
Error
3-
Month
Moving
Forecast
3-
Month
Moving…
Scenario
You have been given a task to create a demand forecast for the second year of sales of a premium outdoor grill.
Accurate forecasts are important for many reasons, including for the company to ensure they have the materials
they need to create the products required in a certain period of time. Your objective is to minimize the forecast
error, which will be measured using the Mean Absolute Percentage Error (MAPE) with a goal of being below 25%.
You have historical monthly sales data for the past year and access to software that provides forecasts based on
five different forecasting techniques (Naïve, 3-Month Moving Average, Exponential Smoothing for .2, Exponential
Smooth for .5, and Seasonal) to help determine the best forecast for that particular month. Based on the given
data, you will identify trends and patterns to create a more accurate forecast.
Approach
Consider the previous month's forecast to identify which technique is most effective. Use that to forecast the next…
Chapter 10 Solutions
Practical Management Science
Ch. 10.2 - Use the RAND function and the Copy command to...Ch. 10.2 - Use Excels functions (not @RISK) to generate 1000...Ch. 10.2 - Use @RISK to draw a uniform distribution from 400...Ch. 10.2 - Use @RISK to draw a normal distribution with mean...Ch. 10.2 - Use @RISK to draw a triangular distribution with...Ch. 10.2 - Use @RISK to draw a binomial distribution that...Ch. 10.2 - Use @RISK to draw a triangular distribution with...Ch. 10.2 - We all hate to keep track of small change. By...Ch. 10.4 - Prob. 11PCh. 10.4 - In August of the current year, a car dealer is...
Ch. 10.4 - Prob. 13PCh. 10.4 - Prob. 14PCh. 10.4 - Prob. 15PCh. 10.5 - If you add several normally distributed random...Ch. 10.5 - In Problem 11 from the previous section, we stated...Ch. 10.5 - Continuing the previous problem, assume, as in...Ch. 10.5 - In Problem 12 of the previous section, suppose...Ch. 10.5 - Use @RISK to analyze the sweatshirt situation in...Ch. 10.5 - Although the normal distribution is a reasonable...Ch. 10.6 - When you use @RISKs correlation feature to...Ch. 10.6 - Prob. 24PCh. 10.6 - Prob. 25PCh. 10.6 - Prob. 28PCh. 10 - Six months before its annual convention, the...Ch. 10 - Prob. 30PCh. 10 - A new edition of a very popular textbook will be...Ch. 10 - Prob. 32PCh. 10 - W. L. Brown, a direct marketer of womens clothing,...Ch. 10 - Assume that all of a companys job applicants must...Ch. 10 - Lemingtons is trying to determine how many Jean...Ch. 10 - Dilberts Department Store is trying to determine...Ch. 10 - It is surprising (but true) that if 23 people are...Ch. 10 - Prob. 40PCh. 10 - At the beginning of each week, a machine is in one...Ch. 10 - Simulation can be used to illustrate a number of...Ch. 10 - Prob. 43PCh. 10 - Prob. 46PCh. 10 - If you want to replicate the results of a...Ch. 10 - Suppose you simulate a gambling situation where...Ch. 10 - Prob. 49PCh. 10 - Big Hit Video must determine how many copies of a...Ch. 10 - Prob. 51PCh. 10 - Prob. 52PCh. 10 - Why is the RISKCORRMAT function necessary? How...Ch. 10 - Consider the claim that normally distributed...Ch. 10 - Prob. 55PCh. 10 - When you use a RISKSIMTABLE function for a...Ch. 10 - Consider a situation where there is a cost that is...
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