A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
The probability distribution of project completion times in simulation-based scheduling
Abstract The assumption of the normality of the distribution of Project Completion Times (PCTs) in simulation-based scheduling has been generally accepted as the norm. However, it is well established in the literature that PCTs are not always normally distributed and that their distribution and variability are affected by the distribution and variability of activity durations. This paper presents an automated risk quantification method that determines the best fit Probability Distribution Function (PDF) of PCTs. The algorithm is programmed in MATLAB and generates a set of simulation outputs obtained by systematically changing the probability distribution functions that define activities’ durations in a network and analyzes the effect of different distributions of activity durations on the distribution of the PCTs. The procedure is described and the findings are presented. This easy-to-use computerized tool improves the reliability of simulation-based scheduling by calculating the exact PDFs of activity durations, simulating the network, and calculating the exact PDF of PCTs. It also simplifies the tedious process involved in finding the PDFs of the many activity durations, and is a welcome replacement for the normality assumptions used by most simulation-based scheduling researchers.
The probability distribution of project completion times in simulation-based scheduling
Abstract The assumption of the normality of the distribution of Project Completion Times (PCTs) in simulation-based scheduling has been generally accepted as the norm. However, it is well established in the literature that PCTs are not always normally distributed and that their distribution and variability are affected by the distribution and variability of activity durations. This paper presents an automated risk quantification method that determines the best fit Probability Distribution Function (PDF) of PCTs. The algorithm is programmed in MATLAB and generates a set of simulation outputs obtained by systematically changing the probability distribution functions that define activities’ durations in a network and analyzes the effect of different distributions of activity durations on the distribution of the PCTs. The procedure is described and the findings are presented. This easy-to-use computerized tool improves the reliability of simulation-based scheduling by calculating the exact PDFs of activity durations, simulating the network, and calculating the exact PDF of PCTs. It also simplifies the tedious process involved in finding the PDFs of the many activity durations, and is a welcome replacement for the normality assumptions used by most simulation-based scheduling researchers.
The probability distribution of project completion times in simulation-based scheduling
Lee, Dong-Eun (author) / Arditi, David (author) / Son, Chang-Baek (author)
KSCE Journal of Civil Engineering ; 17 ; 638-645
2013-05-01
8 pages
Article (Journal)
Electronic Resource
English
The probability distribution of project completion times in simulation-based scheduling
| Online Contents | 2013
Probability of Project Completion Using Stochastic Project Scheduling Simulation
| Online Contents | 2005
Probability of Project Completion Using Stochastic Project Scheduling Simulation
| British Library Online Contents | 2005
Reactive project scheduling: minimizing delays in the completion times of projects
| Online Contents | 2019
Reactive project scheduling: minimizing delays in the completion times of projects
| Springer Verlag | 2019