Please type your work in Microsoft Word. Given that the clew website is not available‚ assignments are to be collected at the beginning of the class on Wednesday‚ October 09‚ 2013. Late assignments are not accepted. This assignment is designed to be individual. Identical assignments will not be graded and automatically assigned a grade of zero. 1. (10 points) You have collected the processing time for five units of Product X at different points in time and the relevant data are shown in the
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SCM 485 Exam 1 Review Forecast Notes Supply Chain Management Sequence of activities and organizations involved in producing and delivering a good or service SCM Define by Council of Supply Chain Management Professionals (CSCMP) Supply Chain Management encompasses the planning and management of all activity involved in sourcing and procurement‚ conversion‚ and all logistics management activities. Importantly‚ it also includes coordination and collaboration with channel partners‚ which can
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the graph that the four-week moving average forecast smoothes the data the most‚ while the naïve forecast responds to change the best. (1 mark) 4.5 Given the following data‚ use exponential smoothing ( = 0.2) to develop a demand forecast. Assume the forecast for the initial period is 5. Exponential Smoothing Forecast Ft = Ft-1 + (At-1 – Ft-1) ie F2 = F1 + (A1 – F1) = 5 + 0.2 (7 – 5) = 5.4. Carrying this through to week 7 gives: Period Demand Exponentially Smoothed Forecast 1 7 5
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period) MAD ≈ 32.403 Exponential Smoothing or ES (adjusted for trend and seasonality) MAD ≈ 13.258 6 Q2: Forecast for January – April 2012 Month Mean Base Period MR SR ES January 0.61 49 825.27 745.12 720.56 February 0.88 50 1107.05 1082.68 1039.50 March 0.87 51 1105.66 1078.04 1027.69 April 1.05 52 1296.43 1310.32 1240.31 7 Q3: Best Forecast: Exponential smoothing forecast has lowest MAD Disadvantages: the exponential smoothing forecast should be updated
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patterns in data can be used to forecast future data points. 1. Moving averages (simple moving average‚ weighted moving average): forecast is based on arithmetic average of a given number of past data points 2. Exponential smoothing (single exponential smoothing‚ double exponential smoothing) - a type of weighted moving average that allows inclusion of trends‚ etc. 3. Mathematical models (trend lines‚ log-linear models
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FORECASTING IN QUANTITATIVE ANALYSIS I am highly honoured to give a presentation on forecasting. You are all welcome. Every organisation’s success depends on how well it is able to forecast. We will look at the meaning of forecast‚ the steps‚ qualitative and quantitative forecasting and finally the benefits. The Meaning Of Forecasting Forecasting is a process of predicting or estimating the future based on past and present data. Forecasting provides information about the potential future events
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a. Use exponential smoothing with a smoothing constant of 0.5 to forecast the population of the United States in 2003. [pic] b. Use exponential smoothing with a smoothing constant of 0.8 to forecast the population of the United States in 2003. c. Which of the two methods provides a more accurate forecast based on the MAD criterion? [pic] 4. Refer to the data provided in problem 1. Using Solver to find the optimal alpha that minimizes MAD‚ use exponential smoothing to forecast
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What are the components of time series (pp 108-109) Which statistic do we use to choose between two forecasting methods In using simple exponential smoothing‚ what do we do if we do not have a forecast for the first period Which component of time series do we smoothen with exponential smoothing With moving averages As a forecasting technique‚ is exponential smoothing always better than moving averages What happens when we increase alpha EMBED Equation.DSMT4 Are we giving more or less
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Which of the following would not be an operations function in a fast-food restaurant? A) advertising and promotion The Dulac Box plant produces 500 cypress packing boxes in two 8-hour shifts. The use of new technology has enabled them to increase productivity by 30%. Productivity is now approximately D) 40.6 boxes/hr. 3.One reason for global operations is to gain improvements in the supply chain. A) True 4.Productivity is the total value of all inputs to the transformation process divided by the
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been taken into consideration. In this paper we are addressing multi-criteria ABC inventory classification and a methodology to standardized each criterion and weight them for classification. The weight for each criterion is based on simple exponential smoothing weight assignments. With inclusion of weight for each criteria and normalizing the data a score is obtained for each item and the classification is done based on the normalized score. The procedure to standardize the criterion and weight is
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