A manager uses the linear trend line Y = 20 +4 t for the last 10 months. Compute for MAPE ifactual demand are as follows.Period123456789сл10O 4.87%O Correct answer is not providedO 6.67%O 5%O 3.88%Actual Demand30323540364550525662

Given : Y = 20+4t where t stands for the respective periods.

Answered: A manager uses the linear trend line Y…

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter10: Introduction To Simulation Modeling

Section10.5: Introduction To @risk

Problem 20P: Use @RISK to analyze the sweatshirt situation in Problem 14 of the previous section. Do this for the...

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Assume the demand for a companys drug Wozac during the current year is 50,000, and assume demand will grow at 5% a year. If the company builds a plant that can produce x units of Wozac per year, it will cost 16x. Each unit of Wozac is sold for 3. Each unit of Wozac produced incurs a variable production cost of 0.20. It costs 0.40 per year to operate a unit of capacity. Determine how large a Wozac plant the company should build to maximize its expected profit over the next 10 years.
Sometimes curvature in a scatterplot can be fit adequately (especially to the naked eye) by several trend lines. We discussed the exponential trend line, and the power trend line is discussed in the previous problem. Still another fairly simple trend line is the parabola, a polynomial of order 2 (also called a quadratic). For the demand-price data in the file P13_10.xlsx, fit all three of these types of trend lines to the data, and calculate the MAPE for each. Which provides the best fit? (Hint: Note that a polynomial of order 2 is still another of Excels Trend line options.)
The file P13_22.xlsx contains total monthly U.S. retail sales data. While holding out the final six months of observations for validation purposes, use the method of moving averages with a carefully chosen span to forecast U.S. retail sales in the next year. Comment on the performance of your model. What makes this time series more challenging to forecast?
Use @RISK to analyze the sweatshirt situation in Problem 14 of the previous section. Do this for the discrete distributions given in the problem. Then do it for normal distributions. For the normal case, assume that the regular demand is normally distributed with mean 9800 and standard deviation 1300 and that the demand at the reduced price is normally distributed with mean 3800 and standard deviation 1400.
Dilberts Department Store is trying to determine how many Hanson T-shirts to order. Currently the shirts are sold for 21, but at later dates the shirts will be offered at a 10% discount, then a 20% discount, then a 40% discount, then a 50% discount, and finally a 60% discount. Demand at the full price of 21 is believed to be normally distributed with mean 1800 and standard deviation 360. Demand at various discounts is assumed to be a multiple of full-price demand. These multiples, for discounts of 10%, 20%, 40%, 50%, and 60% are, respectively, 0.4, 0.7, 1.1, 2, and 50. For example, if full-price demand is 2500, then at a 10% discount customers would be willing to buy 1000 T-shirts. The unit cost of purchasing T-shirts depends on the number of T-shirts ordered, as shown in the file P10_36.xlsx. Use simulation to determine how many T-shirts the company should order. Model the problem so that the company first orders some quantity of T-shirts, then discounts deeper and deeper, as necessary, to sell all of the shirts.
Play Things is developing a new Lady Gaga doll. The company has made the following assumptions: The doll will sell for a random number of years from 1 to 10. Each of these 10 possibilities is equally likely. At the beginning of year 1, the potential market for the doll is two million. The potential market grows by an average of 4% per year. The company is 95% sure that the growth in the potential market during any year will be between 2.5% and 5.5%. It uses a normal distribution to model this. The company believes its share of the potential market during year 1 will be at worst 30%, most likely 50%, and at best 60%. It uses a triangular distribution to model this. The variable cost of producing a doll during year 1 has a triangular distribution with parameters 15, 17, and 20. The current selling price is 45. Each year, the variable cost of producing the doll will increase by an amount that is triangularly distributed with parameters 2.5%, 3%, and 3.5%. You can assume that once this change is generated, it will be the same for each year. You can also assume that the company will change its selling price by the same percentage each year. The fixed cost of developing the doll (which is incurred right away, at time 0) has a triangular distribution with parameters 5 million, 7.5 million, and 12 million. Right now there is one competitor in the market. During each year that begins with four or fewer competitors, there is a 25% chance that a new competitor will enter the market. Year t sales (for t 1) are determined as follows. Suppose that at the end of year t 1, n competitors are present (including Play Things). Then during year t, a fraction 0.9 0.1n of the company's loyal customers (last year's purchasers) will buy a doll from Play Things this year, and a fraction 0.2 0.04n of customers currently in the market ho did not purchase a doll last year will purchase a doll from Play Things this year. Adding these two provides the mean sales for this year. Then the actual sales this year is normally distributed with this mean and standard deviation equal to 7.5% of the mean. a. Use @RISK to estimate the expected NPV of this project. b. Use the percentiles in @ RISKs output to find an interval such that you are 95% certain that the companys actual NPV will be within this interval.
Assume the weight is 0.6 for the most recent period; 0.2 for the second most recent; 0.1 for the third most recent; and 0.1 for the fourth most recent period. Using the four-period weighted moving average technique to predict the demand in February 2019. Find the X and Y values. Dt Ft Period Demand Four-period weighted Moving Average 2014 September 9400 October 10300 November 11200 December 4998 2015 January 9800 7209 February 9555 X March 9800 Y Group of answer choices X = 9899.8; Y = 9778.2 X = 9312.8; Y = 9555.2 X = 9029.6; Y = 9312.8 X = 9555.0; Y = 9313.7 X = 9872.4; Y = 9029.4
The table below comprises of demand from the last 10 months: Month Demand 1 31 2 34 3 33 4 35 5 37 6 36 7 38 8 40 9 40 10 41 Calculate the exponential smoothing with trend forecast for the second month using a alpha and delta of 0.3 each. Take the initial exponentially smoothed forecast (F1) of 30 and initial trend forecast (T1) of 1. Note: I have tried solving this question and I got 31, but unfortunately it was the wrong answer.
Use Excel to make calculations Given the following sales data: Quarter Year 1 Year 2 1 120 150 2 160 200 3 210 250 4 130 170 Compute the seasonal index for each quarter and forecast quarterly demand for year 3 with a projected annual demand of 1000. The efficiency of a production unit is 70 percent. The unit produces an average of 100 products per day. Determine the effective capacity of the unit. The utilization of a machine is 60 percent. The machine has a design capacity of 150 units per hour and an effective capacity of 100 units per hour. Find the efficiency of the machine. FloorsRUs is considering new locations for its manufacturing plants. Costs for constructing a new facility in Huntsville are $1,100,000 and the company estimates that for every product from its new line, there would be an additional cost of $3. If the company were to locate in Hays, the new facility would cost $1,800,000 and each product would incur a $2…
North Dakota Electric Company estimates its demand trend line (in millions of kilowatt hours) to be: D = 80.0 + 0.43Q, where Q refers to the sequential quarter number and Q = 1 for winter of Year 1. In addition, the multiplicative seasonal factors are as follows: Quarter Factor (Index) Winter 0.80 Spring 1.25 Summer 1.45 Fall 0.50 In year 26 (quarters 101-104), the energy use for each of the quarters beginning with winter is (round your response to one decimal place): Quarter Energy Use Winter 98.798.7 Spring nothing
Demand forecasting is the art and science of predicting future market demand.Select one:a. Trueb. False
North Dakota Electric Company estimates its demand trend line (in millions of kilowatt hours) to be: D = 80.0 + 0.43Q, where Q refers to the sequential quarter number and Q = 1 for winter of Year 1. In addition, the multiplicative seasonal factors are as follows: Quarter Factor (Index) Winter 0.80 Spring 1.25 Summer 1.45 Fall 0.50 In year 26 (quarters 101-104), the energy use for each of the quarters beginning with winter is (round your response to one decimal place):

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A manager uses the linear trend line Y = 20 +4 t for the last 10 months. Compute for MAPE if actual demand are as follows. Period 1 2 3 4 5 6 7 8 9 сл 10 O 4.87% O Correct answer is not provided O 6.67% 5% Actual Demand 30 32 35 40 36 45 50 52 56 62