Number of Customers Day Tuesday Wednesday Thursday Friday Saturday Sunday Week 1 Week 2 52 48 36 32 35 30 89 97 98 99 65 69
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A: ANSWER IS AS BELOW:
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Rosa’s Italian restaurant wants to develop forecasts of daily demand for the next week. Th e restaurant is closed on Mondays and experiences a seasonal pattern for the other six days of the week. Mario, the manager, has collected information on the number of customers served each day for the past two weeks. If Mario expects total demand for next week to be around 350, what
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- A Juarez, Mexico, manufacturer of roofing supplies has developed monthly forecasts for a family of products. Data for the 6-month period January to June are presented in the table below. There are 8 hours of production per day. Table 1 Other data Month 1 January 22 Production Demand Days Forecast 950 2 February 18 750 Inventory carrying cost Subcontracting cost per unit Average pay rate Overtime pay Rate 3 March 21 750 4 April 21 1,000 5 May 22 1,300 6 June 20 1,050 Labor-hours per unit Cost of increasing daily production rate (hiring & training) Cost of decreasing daily production rate (layoffs) $5 per unit per month $10 per unit $5 per hour ($40 per day) $7 per hour (above 8 hrs per day) 1.6 hrs per unit $300 per unit $600 per unit This exercise only contains part b. b) Juarez has yet a sixth plan. A constant workforce of 7 is selected, with the remainder of demand filled by subcontracting. Evaluate this plan. The production rate per day = ☐ units. (Enter your response as a whole…The Toro Cutlery Company has collected monthly sales information below: MONTH January February March April The company is examining two forecasting methods, moving average and exponential smoothing for forecasting sales. a. What will the forecast be for January the following year using a three-, four-, and five-month moving averages? Do not round intermediate calculations. Round your answers to the nearest whole number. Forecast (January, 3-month MA): 87667 Forecast (January, 4-month MA): 72500 Forecast (January, 5-month MA): 69600 b. What will the forecast be for January the following year using exponential smoothing with a = 0.6? Assume the forecast for February this year is 25,000. Do not round intermediate calculations. Round your answer to the nearest whole number. SALES 25,000 18,000 43,000 110,000 MONTH May June July August SALES MONTH 84,000 September 28,000 October 97,000 November 58,000 December SALES 27,000 105,000 82,000 76,000The following table shows the actual demand observed over the last 11 years: Year 1 Demand 8 2 9 3 5 This exercise contains only parts b, c, and d. b) Using the 3-year moving average, provide the forecast from periods 4 through 12 (round your responses to one decimal place). Year Forecast 4 5 4 10 6 5 13 7 6 7 8 7 11 9 8 14 10 9 8 11 10 13 12 11 8
- The following table shows the actual demand observed over the last 11 years: Year 1 2 3 4 5 6 7 8 9 10 11 Demand 6 8 4 9 13 8 11 14 9 13 7 Part 2 Using exponential smoothing with α = 0.40 and a forecast for year 1 of 5.0, provide the forecast from periods 2 through 12 (round your responses to one decimal place). Year 1 2 3 4 5 6 7 8 9 10 11 12 Forecast 5.0 5.45.4 6.46.4 5.55.5 6.96.9 9.39.3 8.88.8 9.79.7 11.411.4 10.410.4 11.511.5 9.79.7 Part 3 Provide the forecast from periods 2 through 12 using the naive approach (enter your responses as whole numbers). Year 2 3 4 5 6 7 8 9 10 11 12 Forecast enter your response here enter your response here enter your response here enter your…ABC Inc. sells patio sets. Monthly sales for a seven-month period were as follows: Month Sales (000) Unites Feb 19 Mar 18 Apr 15 May 20 Jun 18 Jul 22 Aug 20 Forecast September sales volume using a weighted average approach using 0.60 for August, 0.30 for July, and 0.10 for June.Forecast based on averages. Given the following data: Period Number of Complaints 1 70 2 75 3 65 4 68 5 74 Prepare a forecast for period 6 using each of these approaches: a. A weighted average using weights of .50 (most recent), .30, .20 b. Exponential smoothing with a smoothing constant of .40
- Given an actual demand this period of 143, a forecast value for this period of 119, and an alpha of .6, what is the exponential smoothing forecast for next period? 123.8 118.2 O 122.2 119.8 O 117.4The following table shows the actual demand observed over the last 11 years: Year 1 2 3 4 5 6 7 8 9 10 11 Demand 6 8 4 10 11 9 12 12 8 13 6 This exercise contains only parts b, c, and d. b) Using the 3-year moving average, provide the forecast from periods 4 through 12 (round your responses to one decimal place). Year 4 5 6 7 8 9 10 11 12 Forecast 66 7.337.33 8.338.33 1010 10.6610.66 1111 10.6610.66 1111 99 c) Using the 3-year weighted moving average with weights 0.15, 0.30, and 0.55, using 0.55 for the most recent period, provide the forecast from periods 4 through 12 (round your responses to two decimal places).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.
- *** Can you please demonstrate how to do parts d, e, f? Given: Year Demand 1 7 2 9 3 5 4 9 5 Predict the value for Year 5: 2 year moving average What is MSE for 2 year moving average? 2 year moving average using 0.6 (weight for the oldest period) and 0.4(weight for most recent period Exponential smoothing, =0.2 and forecast for Year 1 = 5 Linear trend Which forecast method has the least amount of error using MAD? What is the coefficient?Passenger miles flown on Northeast Airlines, a commuter firm serving the Boston hub, are shown for the past 12 weeks: 2 3 21 19 Week 1 Actual Passenger Miles (in thousands) 17 Week Forecasted Passenger Miles (in thousands) a) Assuming an initial forecast for week 1 of 17,000 miles, use exponential smoothing to compute miles for weeks 2 through 12. Use α = 0.2 (round your responses to two decimal places). 10 11 4 5 6 7 8 9 23 18 16 20 18 22 20 15 2 1 3 4 6 7 17.00 17.00 17.80 18.04 19.03 18.83 18.26 5 8 18.61 9 18.49 19.19 10 12 22 11 12Given the following demand data, compute a simple exponential smoothing forecast for alpha values of 0.2 and 0.4. Use the actual value in Period 1 as your starting forecast in Period 2. (Round all answers to two decimal places. Use these rounded answers when computing subsequent answers.) Period Actual Demand 1 2 3 4 5 6 7 8 9 10 11 Period 1 2 3 4 5 6 7 8 9 10 11 12 SESS 10 10 10 10 57 56 оннNUUо 55 55 52 51 51 50 47 49 46 a = 0.2 Forecast α = 0.4 Forecast