Assuming actual product demand were 1,500; 1540; 1,520; 1,550; and 1,560 for Weeks 1, 2, 3, 4, and 5, respectively. Using 2 as interval for moving averages forecasting, the computed sum of percentage error and MAPE should be: * o 1.60% and 15.00% o 2.89% and 0.96% o 1.29% and 0.29% o 0% and 0%
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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.Assuming actual product demand were 1,500; 1540; 1,520; 1,550; and 1,560 for Weeks 1, 2, 3, 4, and 5, respectively. Using 2 as interval for moving averages forecasting, the computed sum of percentage error and MAPE should be: * a. 2.89% and 0.96% b. 1.60% and 15.00% c. 1.29% and 0.29% d. 0% and 0%4 Trinity General Hospital had the following number of patient admissions during the past 8 weeksWeek Patient Admissions1 1202 1453 954 1125 1306 1107 1008 140 a. Develop a 3-week weighted average forecast forWeek 4 through 9 with weightsW1 = 0.2W2 = 0.3W3 = 0.5 b. Forecast patient admissions for week 9 using simpleexponential smoothing with α = 0.2. Assume that the forecast for Week 2 (F2) is the naïve forecast.
- With alpha = 0.8, the Exponential Smoothing (ES) forecast for Month 6 would be: A. 565 haircuts B. 574 haircuts C. 578 haircuts D. 584 haircuts1 The demand for automobiles at Crescent Auto Dealers for the past 8 weeks is as follows. Week Auto Demand Weights1 9 0.12 11 0.33 8 0.64 125 106 137 78 12a Develop a 3-week moving average forecast for Weeks 4 through 9b Develop a 3-week weighted average forecast…1. The Southern Pizza Parlor is a small restaurant. One of the customers' favorites is Southern Spicy Cheesy Pizza. Tim Owan, the manager, must forecast monthly demand for these special pizzas so that he can order the correct amount of pizza shells monthly. Based on records, the demand has been as follows: (Please see the table) a) Forecast the demand for Southern Spicy Cheesy Pizza for month 13-16, using the 3 and 4 period moving average method. Note: Round up all the forecast to the nearest hundredth. b) Forecast the demand for month 16, using weights of 0.5. c) Forecast the demand for month 10 to 16 using the exponential smoothing method with a = 0.3. d) Now, forecast the demand for month 10-16 using the exponential smoothing method with a = 0.6. How do they compare to that in part (c)? Please show your computations
- 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.2. A major airline uses an airport in a large city as a hub for its connecting flights. Each day the airline faces a number of claims from its passengers who lost their baggage. The number of lost baggage claims in the last 14 days have been 67, 25, 57, 58, 35, 29, 77, 44, 38, 36, 23, 69, 53, and 45 a. Use moving average method with N = 3 to forecast the expected number of claims for tomorrow. b. Use exponential smoothing method with parameter α = 0.7 to forecast the number of lost baggage claims that the airline should expect in the next 2 days. c. If the criterion for accuracy is the mean squared error (MSE), which of the forecasting methods in parts (a) and (b) are preferred? d. If you become in charge of providing forecasts for the number of claims in the next 2 days using exponential smoothing method, what would be your point and 90-percent prediction interval forecasts for the number of claims in each of the next 2 days? Use MSE as your evaluation criterion.Given an actual demand this period of 90, a forecast for this period of 58, and an alpha of 0.2, what would the forecast for the next period be using exponential smoothing?
- a) The demand forecast for Month 6 would be: A. 565 haircuts B. 574 haircuts C. 578 haircuts D. 584 haircuts b) With Mean Absolute Deviation (MAD) as the criterion, the best forecasting model for this time series data is: A. Naïve approach B. 2-week Simple Moving Average (SMA) C. Weighted Moving Average (WMA) with weights: 0.5, 0.3, 0.2 D. Exponential Smoothing (ES) with alpha = 0.8Time period Actual sales 1 18 2 22 If the forecasting value of period 3 is 19.6 using exponential smoothing, the smoothing constant is what?4 Trinity General Hospital had the following number of patient admissions during the past 8 weeks Patient Week Admissions 1 120 145 3 95 4 112 5 130 6. 110 7 100 140 Develop a 3-weck weighted average forecast for Week 4 through 9 with weights a W1 = 0.2 W2 = 0.3 W3 = 0.5 Forecast patient admissions for week 9 using simple | exponential smoothing with a = 0.2. Assume that the forecast for Week 2 (F2) is the naïve forecast.