a. Compute a three-semester moving average forecast for semesters 4 through 9. b. Compute the exponentially smoothed forecast (α = 0.2) for the enrollment ata. c. Compare the two forecasts using MAD and indicate the most accurate.
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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.Professor Shethinks Shesverybusy needs to allocate time this week for office appointments, so she needs to forecast the number of students who will seek appointments. The professor has gathered the following time series data recently: Period Student Appointments 4 weeks ago 95 3 weeks ago 80 2 weeks ago 65 Last week 50 What is this week's forecast for student appointments using a three-week moving average? а. 52 b. 80 Ос. 65 d. 78 e. 50 O O O O15. The Vision Hospital is considering the purchase of a new Advance Scan machine. The decision will rest partly on the anticipate patients in the coming months. The numbers of patents during the past years are as follows: Year Number of patents(Actual) 1600 2016 2017 2200 2018 2600 2019 2800 | 2020 3100 Compute the forecast for the year 2021 using exponential smoothing with a forecast for the year 2016 of 1500 and a = .3
- Tom Glass forecasts electrical demand for the FlatlandsPublic Power District (FPPD). The FPPD wants to take itsComstock power plant out of service for maintenance whendemand is expected to be low. After shutdown, performingmaintenance and getting the plant back on line takes two weeks. The utility has enough other generating capacity tosatisfy 1,550 megawatts (MW) of demand while Comstockis out of service. Table 8.5 shows weekly peak demands(in MW) for the past several autumns. When next in year 6should the Comstock plant be scheduled for maintenance?12.4. The chairperson of the department of management at Tech wants to forecast the number of students who will enroll in operations management next semester in order to determine how many sections to schedule. The chair has accumulated the following enrollment data for the past eight semesters: Students Enrolled Semester in OM 1 270 2 310 250 4 290 370 6. 410 7 400 8. 450 a. Compute a three-semester moving average forecast for semesters 4 through 9. b. Compute the exponentially smoothed forecast (a = .20) for the enrollment data. c. Compare the two forecasts using MAD and indicate the most accurate. 3.4 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.
- 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 = 0.8Data collected on the yearly registrations for a Six Sigma seminar at the Quality College are shown in the following table: Year 1 2 3 4 5 7 8 9 10 11 Registrations (000) 5.0 5.0 5.0 4.0 11.0 9.0 6.0 11.0 13.0 16.0 17.0 This exercise contains only parts a and b. a) Using a 3-year moving average, the forecasted registrations (in thousands) for years 4 through 12 are (round your responses to one decimal place): Year 4 6 7 8 10 11 12 Forecast 4.67 6.67 8 8.67 8.67 10 13.33 15.33 b) Using a 3-year weighted moving average in which the registrations in the most recent year are given a weight of 2, and registrations in the other 2 years are each given a weight of 1, the forecasted registrations (in thousands) for years 4 through 12 are (round your responses to one decimal place): Year 4 5 6 7 8 10 11 12 ForecastFigure shows summer air visibility measurements for Denver, Colorado. The acceptable visibility standard is 100, with readings above 100 indicating clean air and good visibility, and readings below 100 indicating temperature inversions caused by forest fires, volcanic eruptions, or collisions with comets.a. Is a trend evident in the data? Which time-series techniques might be appropriate for estimating the average of these data?b. A medical center for asthma and respiratory diseases located in Denver has great demand for its services when air quality is poor. If you were in charge of developing a short-term (say, 3-day) forecast of visibility, which causal factor(s) would you analyze? In other words, which external factors hold the potential to significantly affect visibility in the short term?c. Tourism, an important factor in Denver’s economy, is affected by the city’s image. Air quality, as measured by visibility, affects the city’s image. If you were responsible for development of…
- In the past, Peter Kelle's tire dealership in BatonRouge sold an average of I ,000 radials each year. In the past2 years, 200 and 250, respectively, were sold in fa ll, 350 and 300 inCHAPTER 4 FORECASTING 149winter, ISO and 165 in spring, and 300 and 285 in summer. With amajor expansion planned, Kelle projects sales next year to increaseto I ,200 radials. What will be the demand during each season? ~(Mylab Operations Management also includes a shorter (brief)version of this problem.)12.2 The manager of the I-85 Carpet outlet needs to be able to forecast accurately the demand for Soft Shag carpet (its biggest seller). If the manager does not order enough carpet from the carpet mill, customers will buy their carpets from one of the outlets many competitors. The manager has collected the following demand data for the past 8 months. Month 1 2 3 4 5 6 7 8 Demand for Soft Shag Carpet (1000 yd) 5 10 6 8 14 10 9 12 a. Compute a three-month moving average forecast for months 4 through 9.4 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.