manager is attempting to put together an aggregate plan for the coming nine months. She has obtained a forecast of expected demand for the planning horizon. The plan must deal with highly seasonal demand; demand is relatively high in periods 3 and 4 and again in period 8, as can be seen from the following forecasts: Period 1 2 3 4 5 6 7 8 9 Total Forecast 1 2 3 4 5 6 7 8 9 TOTAL 190 230 260 280 210 170 160 260 180

Zeus Computer Chips, Incorporated used to have major contracts to produce the Centrino-type chips. The market has been declining during the past three years because of the quad-core chips, which it cannot produce, so Zeus has the unpleasant task of forecasting next year. The task is unpleasant because the firm has not been able to find replacement chips for its product lines. Here is demand over the past 12 quarters: QUARTER TWOYEARS AGO DEMAND QUARTER LASTYEAR DEMAND QUARTER THISYEAR DEMAND 1 4,800 1 3,500 1 3,200 2 3,500 2 2,700 2 2,100 3 4,300 3 3,500 3 2,700 4 3,000 4 2,400 4 1,700 Use the regression and seasonal indexes to forecast demand for the next four quarters. Note: Do not round intermediate calculations. Round your answers to 2 decimal places. Period                              Forecast 1 2 3 4

PROBLEM 2:The manager of a large manufacturer of industrial pumps prepare forecasts for a six- month period.  Month Demand Forecast     1     492               488     2     470   484     3     485               480     4     493               490     5     498               497     6                 492   493 Required: Compute for the MAD, MSE, and MAPE.

Please do not give solution in image format thanku

A store has the following demand figures for the last four years: Year Demand 100 1 150 3 112 4 200 Given a demand forecast for year 2 of 100, a trend forecast for year 2 of 10, an alpha of 0.3, and a beta of 0.2, what is the demand forecast for year 3 using the exponential smoothing with trend method? 128 115 Ⓒ 135 Ⓒ 145

Dave's Bar-B-Q operated a moble kitchen that serviced construction sitos, office buildings, and public parks. Beginning in June, snow cones were added to the menu. The weekly sales figures for June of the previous year are given in the following chart Forecast (alpha=0.3) 5.0 Week Sales 4. 4.7 3 4 Use exponential smoothing, a smoothing coefficient of 0.3, to forecast demand for the third week of June. O A. 4.7 O B. 6.4 OC. 5.1 OD. 4.0

(a) Suppose the data in the table below represents total revenues (in $ millions) for one real estate agency in the GTA. Fill in the 3-year Moving Averages, Weighted Moving Averages (with weights 5,3,2 starting from the most recent time period), and the Exponential Smoothing Forecast values in the table below: Round your answers in part (a) to 2 decimal places. Year Revenue 3-Year Moving Averages Weighted Moving Averages Exponential Smoothing α=0.35α=0.35 2016 4.7       2017 4.9       2018 5.4       2019 5.9       2020 6.7       2021 7.9       2022 Forecast           Round your answers in part (b) to 2 decimal places, and round the MAD/MAE to 3 decimal places. (b) Calculate the MAD/MAE for 3-year Moving Averages for 2019-2021 (use results from the previous problem). Year Revenue 3-Year Moving Averages Absolute Error 2016 4.7     2017 4.9     2018 5.4     2019 5.9     2020 6.7     2021 7.9         MAD/MAE =   Round your answers in part (c) to 2…

2. Fastway is a parcel delivery company based in Pretoria. It measures demand on a weekly basis in terms of the number of parcels which it is given to deliver (irrespective of the size of each parcel). The forecast for week 20 is 63. The table below shows actual demands for Fastway. Week Actual demand 20 63 21 62 22 67 23 66 24 67 25 69 26 65 27 71 28 68 29 68 30 70 31 72 32 66 33 68 34 67 Predict the forecast for week 35 using an exponential smoothing with a smoothing constant of 0.20.

The purpose of this assignment is to utilize Distribution Requirements Planning (DRP) parameters and inventory data to determine planned order releases in central warehouses. address each problem using full sentences and proper spelling and grammar and submit in an Excel template. 2. For the warehouse of Figure 14.8, suppose actual demands were 24, 16, and 18 in periods 1, 2, and 3, respectively. The initial DRP record is: Forecast requirements In transit Projected available balance Planned shipments Q=40; lead time=1; SS=6. 6 1 20 40 26 Period 2 3 4 5 20 20 20 20 6 266 26 40 40 a. Create the other three DRP records as done in Figure 14.8. What problem is created in period 2? What can be done? b. Does error addback work for this set of circumstances?

A store’s demand figures are given in the table. According to this, what is the linear regression forecast for Week 12?