Enhancing programevaluation and review technique (PERT) for construction project scheduling with Bayesian updating and appropriate probability distributions

Abstract

The Program Evaluation and Review Technique (PERT) is a popular scheduling technique that takes advantage of the Beta distribution to present uncertainty in activity durations. This study presents an advanced PERT method with an improved Bayesian updating and improved assumed prior distributions, which better represent real-world projects. The method is backed with detailed mathematical proofs and derivations for a solid theoretical foundation. A numerical case study involving a 30-floor building construction project is used to compare the performance of traditional PERT, the Beta-improved Bayesian PERT, and the Log-Normal Bayesian PERT methods. In the example, the activities considered are Formwork, Rebar and Construction, Masonry, Mechanical-Electrical-Plumbing (MEP), and Finishing, which are the main activities in a construction project. The results show that the Beta-improved and the Log-Normal distributions are constructed successfully in the models with converging variance – an observation that delineates the uncertainty reduced along a real project’s course. With enhanced functions, the PERT method can be utilized to support project decision-makers in scheduling and managing complex projects in reality.