a. Using a three-week moving average, what would you forecast the next week to be number.) Forecast for the week 5
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- A manager would like to know the total cost of a chase strategy that matches the forecast belowusing a steady regular production rate of 200 units a month, a maximum of 20 units per month ofovertime, and subcontracting as needed to make up any shortages. The unit costs are:Regular production = $35Overtime = $70Subcontracting = $80Month 1 2 3 4 5 6Forecast 230 200 240 240 250 240Assume 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 = 9029.4Matrix uses simple exponential smoothing with S.F = 0.6 to forecast demand. The forecast for the week of Nov 1 was 350 units, whereas the actual demand turned out to be 400 units. Forecast the demand for the week of Nov 8 to week Nov 22 Week Actual Demand Forecast Nov 01 350 400 Nov 08 460 430 Nov 15 501 448 Nov 22 495 479.8 Element of Competency Determine the quantity of raw materials and other products order.
- The following are historical demand data: YEAR SEASON ACTUALDEMAND 2011 Spring 203 Summer 144 Fall 382 Winter 565 2012 Spring 471 Summer 271 Fall 686 Winter 955 Use regression analysis on deseasonalized demand to forecast demand in summer 2013. (Do not round intermediate calculations. Round your answer to the nearest whole number.)Exercise 2: The Patio, Inc. company manufactures patio furniture. From experience, you know that demand is seasonal, that is, there is a greater amount of demand for products in specific periods throughout a year of operations. In order to properly plan its production for the next year, the furniture sales (in units) for the previous two years were reviewed: 20X3 20X4 Seasonal index Average seasonal index 20X5 First quarter (Jan-Feb-Mar) 94,700 103,500 ¿? ¿? ¿? Second Quarter (Apr-May-Jun) 116,000 126,100 ¿? ¿? ¿? Third quarter (Jul-Aug-Sep) 152,500 166,200 ¿? ¿? ¿? Fourth quarter (Oct-Nov-Dec) 101,225 90,000 ¿? ¿? ¿? Use the multiplicative seasonal method to make a forecast for the year 20X5 based on the sales force estimate, which determined that the demand for furniture will be 15% higher than in the year 20X4. Calculate the average number of units sold per station.Calculate the seasonal index.Calculate the…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 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).
- Use regression analysis on deseasonalized demand to forecast demand in Summer of Year 3, given the following historical demand data: Year Season Actual Demand 1 Spring 205 Summer 140 Fall 375 Winter 575 2 Spring 475 Summer 275 Fall 685 Winter 965Week Demand of beef 1 500 2 550 3 600 4 720 5 780 6 800 Corresponding weights are W1=0.6, W2=0.4 and W3=0.3 The 3-week weighted moving average to forecast- Week Demand of beef 3- weeks weighted moving average forecast 1 500 2 550 3 600 4 720 (500×0.6+550×0.4+600×0.3) / (0.6+0.4+0.3) = 538.46 5 780 (550×0.6+600×0.4+720×0.3) / (0.6+0.4+0.3) = 604.61 (600×0.6+720×0.4+780×0.3) / (0.6+0.4+0.3) = 678.46 Forecast for week 4,5 and 6 = 538.46, 604.61 and 678.46 4-week weighted moving average to forecast- Corresponding weights are W1=0.6, W2=0.4, W3=0.3, and W4=0.2 Week Demand of beef 4-weeks weighted moving average forecast 1 500 2 550 3 600 4 720 5 780 (500×0.6+550×0.4+600×0.3+720×0.2) / (0.6+0.4+0.3+0.2) = 562.66 (550×0.6+600×0.4+720×0.3+780×0.2) / (0.6+0.4+0.3+0.2) = 628 Forecast for week 6 and 7 = 562.66, 628…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.
- Not all the items in your office supply store are evenly distributed as far as demand is concerned, so you decide to forecast demand to help plan your stock. Past data for legal-sized yellow tablets for the month of August are Week 1 250 Week 2 350 Week 3 550 Week 4 650 a. Using a three-week moving average, what would you forecast the next week to be? b. Using exponential smoothing with α = 0.30, if the exponential forecast for week 3 was estimated as the average of the first two weeks [(250 + 350)/2 = 300], what would you forecast week 5 to be?Demand forecasting is the art and science of predicting future market demand.Select one:a. Trueb. FalseSerena just visited a restaurant for dinner. During the dinner time, she overheard two customers saying that company TXL will expect its workforce to go on strike next week, which will halt manufacturing and distribution of products. When Serena gets back home, she immediately uses this information to update her analyst forecast on company TXL from a “buy” to a “sell”. Please explain which Standard is violated.