Bootstrap Technique for Risk Analysis with Interval Numbers in Bridge Construction Projects

Abstract

Bridges are principal and vital transportation structures. If risk management is not considered in bridge construction projects, objectives cannot be delivered on time, on budget, or with suitable quality results. Risk data set sizes and experts’ judgments are not usually sufficient for analyzing significant risks in bridge construction projects; moreover, the statistical distributions for risk parameter estimates are usually unknown. Standard parametric statistical techniques cannot provide appropriate solutions for cases with small data sets or unknown distributions. This paper proposes a new hybrid approach by using a nonparametric resampling technique and interval computations for risk analysis, in particular, for bridge construction projects. Bootstrap techniques produce more accurate inferences for comparing parametric techniques and are an alternative when the underlying parametric assumptions are not considered. Increasingly, because of the complexity and uncertainty in decision making at bridge projects, it is easier or more natural to provide interval values for parts or all of decision-making judgments. Furthermore, the goal of reducing standard deviations for both risk probability and risk impact compared with the conventional approach is another conclusion of this paper. The proposed approach is applied to a case in Iran to show the validity of the approach.