A Combined Approach to Enhance Risk Management in Building Information Modelling in Iran's Construction Industry

Abstract

Along with the emergence of new technologies in recent years, risks and uncertainties have become more complex. Although Building Information Modelling (BIM) is a promising method in the construction industry that can mitigate numerous risks, it also introduces new risks as an innovative technology. Therefore, improving risk management through BIM for the construction works is of great importance. The present study utilized a four-stage combined approach for this purpose. Initially, the most significant risks in BIM implementation in the construction industry were identified. Subsequently, the causal relationships among the risks were identified using the DEMATEL method, and the importance of each risk was determined using the Analytic Network Process (ANP). Finally, a mathematical model was developed to allocate responses to the risks, and the mathematical model was solved using the Invasive Weed Optimization (IWO) and Grey Wolf Optimizer (GWO) algorithms. The analysis revealed that the objective function value obtained through the Grey Wolf Optimizer method was consistently more favourable compared to the Invasive Weed Optimization method. Ultimately, the findings indicated that the proposed approach serves as a powerful tool for project managers to assess risks and predict appropriate responses for the risks of BIM implementation.