Modeling and Optimization of Quantitative Risk in Fast-Track Infrastructure Development Projects

The construction industry increasingly adopts the fast-tracking approach to meet the growing demand for rapid delivery of infrastructure projects. However, overlapping activities inherent in the fast-track strategy introduce distinctive risks or alter existing risk characteristics, leading to “overlapping risks.” This study develops a quantitative risk assessment and simulation model to evaluate the economic impact of overlapping risks in fast-track infrastructure projects. The proposed model integrates Monte Carlo simulation with a proprietary optimization engine to assess the influence of overlapping risks on project duration and cost under three different overlapping degrees. A commercial renovation project serves as the case study for model demonstration. Results indicate that overlapping risks can significantly increase total project costs, despite a high probability of meeting target durations. Eight critical risks were identified as major drivers of project performance, affecting duration, cost, or both. The optimization procedure further reveals that the best mitigation strategy involves a combination of varying overlapping degrees to minimize economic impacts while achieving the target schedule. This research contributes a robust decision-support model for fast-track project planning by explicitly quantifying overlapping risks, capturing their probabilistic impact distributions, and highlighting interdependencies among risks.