| Title |
Advanced Stochastic Simulation-based Scheduling System (AS3) for Improving Usability in Practice |
| Authors |
Kim Ryul-Hee ; Bae Tae-Hyun ; Lee Dong-Eun |
| Keywords |
CPM ; Simulation ; Scheduling ; Stochastic Probability Theory ; Project Completion Time ; MATLAB |
| Abstract |
This paper introduces an automated tool named Advanced Stochastic Simulation-based Scheduling system(AS3). The system automatically integrates CPM schedule data exported from P3 into it and computes the best fit Probability Distribution Functions (PDFs) of historical activity duration data. In addition, it defines activity durations using the PDFs identified, simulate the schedule network, and estimates the best fit PDF of project completion times (PCTs). AS3 integrates the automated best fitting function which identifies the exact distribution of PCTs using the “goodness of fit” principles into existing simulation-based scheduling method. It improves the reliability of simulation-based scheduling by effectively dealing the uncertainties of the activity durations rather than existing systems dose. Furthermore, it increases the usability of the schedule data obtained from commercial CPM softwares, and effectively handle the variability of the PCTs by finding the best fit PDF of PCTs. It is implemented as an easy-to-use computerized tool programmed in MATLAB. AS3 can make significant contribute to the field of simulation-based scheduling, because (1) it analyzes the effect of different distributions of activity durations on the distribution of the PCTs, (2) the reliability obtained by the system is higher than conventional simulation-based scheduling systems, (3) simplifies the tedious and burdensome process involved in finding the PDFs of the many activity durations, and (4) it is a welcome replacement for the normality assumptions used by most simulation-based scheduling researchers, and therefore increase the usability of simulation-based scheduling and generates more accurate results. |