Combining Monte Carlo simulation and Bayesian networks methods for assessing completion time of projects under risk

Abstract

In this study, Monte Carlo simulation and Bayesian network methods are combined to present a structure for assessing the aggregated impact of risks on the completion time of a construction project. Construction projects often encounter different risks which affect and prevent their desired completion at the predicted time and budget. The probability of construction project success is increased in the case of controlling influential risks. On the other hand, interactions among risks lead to the increase of aggregated impact of risks. This fact requires paying attention to assessment and management of project aggregated risk before and during the implementation phase. The developed structure of this article considers the interactions among risks to provide an indicator for estimating the effects of risks, so that the shortage of extant models including the lack of attention to estimate the aggregated impact caused by risks and the intensifying impacts can be evaluated. Moreover, the introduced structure is implemented in an industrial case study in order to validate the model, cover the functional aspect of the problem, and explain the procedure of structure implementation in detail.