Water Resources and Power

The program evaluation review technique(PERT) is a key project management tool frequently used for scheduling in complex projects. However, the traditional PERT model assumes that all process durations follow a single distribution(the Beta distribution), that processes are independent of each other, and that critical paths are fixed. These assumptions diverge from actual engineering conditions, limiting the accuracy of construction period simulations. To address these limitations, this paper introduces an optimized PERT model based on the Clayton Copula function. Firstly, the model identifies the distribution forms of various types of processes by fitting historical data, thus revealing the diversity in process duration distributions. Secondly, for the dependency relationships that exist between adjacent processes, Spearman's rank correlation coefficient is used to quantitatively describe the correlations between them. On this basis, the joint distribution of adjacent process durations is constructed using the Clayton Copula function. The Monte Carlo(MC) method is applied to simulate process durations, critical paths, and construction period distributions, enabling the identification of criticality indicators for both critical paths and processes. Case studies have shown that the model can accurately reflect the distribution characteristics of process durations and the correlations between adjacent processes, effectively identify critical paths, and accurately simulate the distribution of project construction periods, which can provide reliable decision support for project schedule management.