Project Management: Resource Allocation Questions involving early start's, late start's, cost, and crital paths.

Consider the following network for conducting a two-week (10 working days) computer training class: (Network in the attached file) A. Construct a schedule for the following Crash/Normal Schedule chart below: 1. Early start's for all activities 2. Late start's for all activities 3. Slacks for all activities 4. The critical path B. Provide the following: 1.   Find the crash cost per day 2.   Which activities should be crashed to meet a project deadline of 10 days with a minimum cost? Assume partial crashing. 3.  Find the new cost 4.   Is partial crashing an appropriate assumption in this kind of project? What problems ... click for more

There are many types of naà¯ve forecasts. Simple (next period same as this period), change (rate of growth determined by change between two period). In this situation, it appears that a simple naà¯ve forecast is required. In this case, demand at period 1 = 90, which will be the same for all subsequent periods. Period-----Demand-------Naà¯ve Forecast 1--------------90-----------------90 2--------------85-----------------90 3--------------91-----------------90 4--------------92-----------------90 5--------------95-----------------90 6--------------88-----------------90 You can now use such measures as MAD (Mean Absolute Deviation), MSE (Mean Square Error) etc. to determine which forecast provided a better fit. MAD (Naà¯ve) = (abs(90-90) + abs(85-90) + … +abs(88-90))/6 = 2.5 MAD (Forecast) = 3.67. Using MAD, the naà¯ve forecast would have been better.

A manager has been using a certain technique to forecast demand for word processing units for the past six periods. Actual and predicted amounts are shown below. Would a naive forecast have produced better results? Period--------Demand-------Forecast 1---------------90----------------87 2---------------85----------------88 3---------------91----------------87 4---------------92----------------89 5---------------95----------------90 6---------------88----------------92

Developing an equation and determine the correlation coefficient from a given data set. Solution attachment in Word.

Use linear regression to develop a predictive model for demand for ironing board covers based on sales of irons. Year--------Sales of Irons (000)----Demand for Covers (000) 1---------------8-------------------------------5 2---------------7-------------------------------2 3--------------- 10------------------------------- 6 4--------------- 6------------------------------- 4 A) Develop the equation. B) What is the coefficient of correlation for this data?

Predicting demand: 3-period moving average, exponential smoothing, calculating MAD.

Demand for the last four months was: Month ----Mar-Apr-May-Jun Demand-----6---8-----10---8 A) Predict the demand for July using each of these methods: 1) A 3-period moving average 2) Exponential smoothing with alpha equal to 0.20 B) If the naive approach had been used to predict demand for April through June, what would the MAD have been for those months?

Calculating a forecast using a trend adjusted smoothing. Solution attachments in Word and Excel.

The business analyst for Ace Business Machines, Inc. wants to forecast this year's demand for manual typewriters based on the following historical data: TIME PERIOD-------DEMAND 5 years ago---------------900 4 years ago--------------- 700 3 years ago--------------- 600 2 years ago--------------- 500 Last year---------------- 300 What is the forecast for this year using trend adjusted (double) smoothing with alpha(1) = 0.3 and alpha(2) = 0.2, if the forecast for last year was 310, the forecast for two years ago was 430, and the trend estimate for last year's forecast was -150? * Please use 310, 430,... click for more