A chain of pizza stores has had the following sales for take-out food over the last four evenings-Monday, Tuesday, Wednesday, and Thursday-of 29, 25, 35, and 30 pizzas, respectively. What would be their forecast for Friday using a naïve forecasting approach? Select one: a. 30 pizzas. b. 35 pizzas. c. 29.8 pizzas. d. 25 pizzas.
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- At the beginning of each week, a machine is in one of four conditions: 1 = excellent; 2 = good; 3 = average; 4 = bad. The weekly revenue earned by a machine in state 1, 2, 3, or 4 is 100, 90, 50, or 10, respectively. After observing the condition of the machine at the beginning of the week, the company has the option, for a cost of 200, of instantaneously replacing the machine with an excellent machine. The quality of the machine deteriorates over time, as shown in the file P10 41.xlsx. Four maintenance policies are under consideration: Policy 1: Never replace a machine. Policy 2: Immediately replace a bad machine. Policy 3: Immediately replace a bad or average machine. Policy 4: Immediately replace a bad, average, or good machine. Simulate each of these policies for 50 weeks (using at least 250 iterations each) to determine the policy that maximizes expected weekly profit. Assume that the machine at the beginning of week 1 is excellent.Under what conditions might a firm use multiple forecasting methods?The Baker Company wants to develop a budget to predict how overhead costs vary with activity levels. Management is trying to decide whether direct labor hours (DLH) or units produced is the better measure of activity for the firm. Monthly data for the preceding 24 months appear in the file P13_40.xlsx. Use regression analysis to determine which measure, DLH or Units (or both), should be used for the budget. How would the regression equation be used to obtain the budget for the firms overhead costs?
- Sales of the Crown Gems have been increasing over the past five years. The operations manager has estimated sales in 2017 to be 410 Crown Gems. Using exponential smoothing with a weight of α = 0.30, the forecasts for 2017 through 2022 were developed. The forecasts for 2017 through 2022 is: Year Forecast 2016 450 2017 450 2018 463.5 2019 479.85 2021 504.795 2022 528.5565 a. Advise Crown Gems of the benefits associated with this method of forecasting. b.Caution the manager on the limitations associated with your forecast.The following company sells two family of products. The company begins its roll-up forecast anticipating a need for 60 units of A1 and 75 units of A2 at a cost of $200 per unit and $350 per unit, respectively. In addition, they anticipate a need for 85 units of B1 and 90 units of B2 at a cost of $410 per unit and $525 per unit respectively. Complete the roll-up pyramid forecasting technique for MPC Inc. Fill all the blanks. Allow 1 decimal value.Harlen Industries Limited has a simple forecasting model whose forecast demand has been plotted against actual demand for an 8 months duration. The firm uses an average weekly demand which is shown below: WEEK FORECAST DEMAND ACTUAL DEMAND 1 140 135 2 150 160 3 165 155 4 170 175 5 155 180 6 160 150 7 170 145 8 135 140 Compute the Mean Absolute Deviation (MAD) of the Harlen industries limited? Calculate the Mean Square Error (MSE) for Harlen industries Limited? Calculate the Cumulative Forecast Error (CFE) of Harlen industries limited?
- If the demand in the current week was 102 units and we had forecast it to be 125, what would be next week’s forecast using an exponential smoothing model with an alpha of 0.3?The following table gives the number of pints of type A blood used at Damascus Hospital in the past 6 weeks: Week Of August 31 September 7 September 14 September 21 September 28 October 5 a) The forecasted demand for the week of October 12 using a 3-week moving average = 373.33 pints (round your response to two decimal places). b) Using a 3-week weighted moving average, with weights of 0.20, 0.25, and 0.55, using 0.55 for the most recent week, the forecasted demand for the week of October 12 = 373.3 pints (round your response to two decimal places and remember to use the weights in appropriate order the largest weight applies to most recent period and smallest weight applies to oldest period.) Week Of c) If the forecasted demand for the week of August 31 is 360 and a = 0.30, using exponential smoothing, develop the forecast for each of the weeks with the known demand and the forecast for the week of October 12 (round your responses to two decimal places). August 31 September 7…Three years ago CMSV admissions office began using exponential smoothing with a smoothing constant of 0.25 to forecast the number of applications for admissions each year. Based on the previous experience, this process was begun with an initial estimate of 5000 applications. The actual number of applications turned out to be 4600 in the first year and grew to 5300 in the second year and 6000 last year. Determine the forecasts that were made for each of the past three years. Calculate MSE and MAD for these three years and determine the forecast for the next year.
- The number of internal disk drives (in millions) made at a plant in Taiwan during the past 5 years follows: Year Disk Drives 1 138 2 156 3 184 4 202 220 a) Using simple linear regression, the forecast for the number of disk drives to be made next year = 211 disk drives (round your response to one decimal place). b) The mean squared error (MSE) when using simple linear regression = drives- (round your response to one decimal place). c) The mean absolute percentage error (MAPE) when using simple linear regression = % (round your response to one decimal %3D place).The following table gives the number of pints of type A blood used at Damascus Hospital in the past 6 weeks: Week Of August 31 September 7 September 14 September 21 September 28 October 5 a) The forecasted demand for the week of October 12 using a 3-week moving average = pints (round your response to two decimal places). b) Using a 3-week weighted moving average, with weights of 0.20, 0.30, and 0.50, using 0.50 for the most recent week, the forecasted demand for the week of October 12 = largest weight applies to most recent period and smallest weight applies to oldest period.) c) If the forecasted demand for the week of August 31 is 345 and x = 0.30, using exponential smoothing, develop the forecast for each of the weeks with the known demand and the forecast for the week of October 12 (round your responses to two decimal places). Week Of August 31 September 7 September 14 September 21 September 28 October 5 October 12 Pints Used 345 370 408 383 371 374 Pints Used 345 370 408 383 371…