A new approximation algorithm for obtaining the probability distribution function for project completion time

✍ Scribed by Ming-Jong Yao; Weng-Ming Chu

• Publisher: Elsevier Science
• Year: 2007
• Tongue: English
• Weight: 994 KB
• Volume: 54
• Category: Article
• ISSN: 0898-1221
• DOI: 10.1016/j.camwa.2007.01.036

✦ Synopsis

This paper focuses on the application of the techniques of discretization to obtain an approximated probability density function (pdf ) for the completion time of large-size projects, in which we allow any type of pdf for the duration of activities. In this study, we improve the techniques of discretization in the following two ways: first, we propose to replace the max operation with an approximation procedure to save significant computational loading; and second, to reduce the error from assuming independence between paths using a simple heuristic rule. To evaluate the performance of our proposed algorithm, we randomly generated 20 sets of 100-node instances in our numerical experiments. Taking the results from a Monte Carlo simulation using 20,000 samples as a benchmark, we demonstrate that the proposed algorithm significantly outperforms the PERT model and Dodin's [B.