Probabilistic Integration of Cost and Schedule Risk Management in Construction Engineering: A Monte Carlo Framework for Enhanced Owner Decision-Making

Abstract

Using probabilistic approaches to combine cost and scheduling risks is now necessary for good building project management. Traditional deterministic methods typically don't take into account the uncertainties and connections between time and cost, which can lead to wrong predictions and bad decisions. This study looks at how to use Monte Carlo Simulation as a strong tool for probabilistic integration, which lets project owners look at a range of possible outcomes and how likely they are to happen. The study shows how early involvement, risk-informed decision-making, and active risk governance can help with better project planning and control by focusing on the owner's key role. Owners may better manage uncertainties, assign contingencies, and make projects more resilient by using advanced risk management tools and encouraging a culture of collaboration around risk. The results show that construction risk management is moving toward data-driven, predictive analytics, which will lead to more dependable and efficient project delivery.