Fast and accurate risk evaluation for scheduling large-scale construction projects

Dho Heon Jun, Khaled El-Rayes

Research output: Contribution to journalArticlepeer-review


This paper presents the development of a novel probabilistic scheduling model that enables fast and accurate risk evaluation for large-scale construction projects. The model is designed to overcome the limitations of existing probabilistic scheduling methods, including the inaccuracy of the program evaluation and review technique (PERT) and the long computational time of the Monte Carlo simulation method. The model consists of three main modules: PERT model; fast and accurate multivariate normal integral method; and a newly developed approximation method. The new approximation method is designed to focus the risk analysis on the most significant paths in the project network by identifying and removing insignificant paths that are either highly correlated or have high probability of completion time. The performance of the new model is analyzed using an application example. The results of this analysis illustrate that the new model was able to reduce the computational time for a large-scale construction project by more than 94% while keeping the error of its probability estimates to less than 3%, compared with Monte Carlo Simulation methods.

Original languageEnglish (US)
Pages (from-to)407-417
Number of pages11
JournalJournal of Computing in Civil Engineering
Issue number5
StatePublished - Sep 2011


  • Construction planning
  • Network analysis
  • Project management
  • Risk management
  • Scheduling
  • Simulation models
  • Stochastic models

ASJC Scopus subject areas

  • Computer Science Applications
  • Civil and Structural Engineering


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