Schedule Default Distributions and Bayesian Estimation in Airport Construction Master Schedule Management

Abstract:

Based on the WBS(work breakdown structure) in practice, a probability distribution of delayed activity frequency is proposed to depict schedule default risks in different subsystems of airport construction project from an overall and systematic perspective. Considering the lack of schedule default data, Bayesian methods are employed to estimate the distribution parameters. In particular, MCMC (Markov chain Monte Carlo) simulations are applied as computational scheme to obtain Bayesian estimates. The research process shows the way to model schedule default risks for different subsystems of airport construction project. The application of the MCMC method to estimate the parameters shows advantages in robustness according to different choices of distributions. The use of Bayesian methods makes it possible to integrate qualitative information, and constantly update the model during the construction in the future.