Confidence percentile estimation to cost and schedule integration based on Monte Carlo multiple simulation analysis technique

Using independent estimating techniques, the high confidence percentile estimating values for cost and schedule can't be gained simultaneously, and the cost risk and the schedule risk are increasing in the actual projects. The integration method combines Monte Carlo multiple simulation analysis technique, regression analysis and statistical analysis. First, the project with stochastic cost and duration in activities was simulated m times using n runs per simulation. Then, the simulation outputs of cost and schedule were analyzed. The 95th percentile project cost (or schedule) value, its corresponding schedule (or cost) value, and the percentile ranking of the schedule (or cost) were recorded, and the conditional percentile ranking of the schedule (or cost) values were determined. Finally, in order to quantify the relationship existing between the percentile ranking of the schedule (or cost) and its corresponding schedule (or cost) value, the regression analysis models about them were founded and compared, and the high confidence percentile estimating values for cost and schedule were required simultaneously.