Abstract
The main objective of this study is to help the project managers for making better informed decisions in the form of corrective and/or preventive actions through developing a probabilistic time forecasting model, which is generated on the basis of the beta distribution as a curve fitting technique, and to provide a better basis for the schedule performance control and for the risk management of on-going projects. Four projects has been generated and used to validate the time prediction generated from the all models through the different periods of actual completion. The beta forecasting model (BFM) has been programmed in a graphical user interface (GUI) for Matlab (R2009a) and it can be implemented on all types of projects. A comparative study reveals that the BFM provides much more accurate forecasts than those are generated from the conventional methods, forecasts the completion dates on the basis of analyzing the summary of project-level data, and has accurate forecasts as the critical path method (CPM) does.
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