A Mathematical Framework Based on Monte Carlo Simulation and Entropy-TOPSIS for Quantitative Risk Prioritization in Construction Projects

Construction projects often face significant uncertainty due to technical and organizational complexity. Although various methods exist for risk assessment, few integrate probabilistic simulation with multi-criteria decision-making to address uncertainty comprehensively. This study fills this gap by proposing a hybrid framework that combines Monte Carlo simulation, entropy weighting, and the TOPSIS method to assess and rank construction risks. The model evaluates risks based on key criteria such as cost, time, safety, and environmental impact. Results highlight safety-related risks as the most critical, followed by equipment failure and financial constraints. The proposed approach enhances risk analysis accuracy and provides practical support for decision-making in uncertain project environments.

Keywords:

Risk Management , Construction Projects , Monte Carlo Simulation , TOPSIS , Uncertainty Modeling , Decision-Making