Simulation-based approach to quantify the impact of stochastic time-window constraints on construction schedules and budgets for remote cold regions

Abstract

This study addresses the planning and scheduling challenges of construction projects in environments with strict climate-induced time constraints, such as winter road availability and temperature-dependent work windows. The research focuses on assessing risks to project timelines and budgets by analyzing historical meteorological and winter road data to model uncertainties in the start and end dates of these critical time windows. The project schedule is developed based on technological and precedence relationships, while adhering to environmental constraints. Risks are evaluated solely in terms of time-window variability, excluding other uncertainties such as crew productivity or activity duration changes. Deterministic project baselines are established using averaged historical data for time-window boundaries as the base case. A Monte Carlo simulation then samples open and close dates from fitted probability distributions to quantify schedule and budget risks relative to this baseline. Monte Carlo simulation of stochastic winter-road and thawing time windows for the Northwest Territories bridge case study shows an 84.78% probability of completing the project within the 654-day target schedule and a 21.08% probability of staying under the $28.5 million target budget. The joint probability of meeting both targets is 20.72%. Shorter winter-road windows at project start substantially increase total costs, demonstrating that climate variability significantly affects sequencing, resource allocation and overall project risk in remote cold regions. This research introduces a novel simulation-based framework for quantifying climate-related risks in cold-region construction, extending prior time-window methods with stochastic modelling. It offers a foundational risk-informed approach, with the potential to incorporate additional uncertainties like productivity fluctuations or alternative methods in future studies.