A Network-based Simulation Model for Helicopter Rescue Time Estimation in the Canadian Arctic

Abstract

Search-and-rescue (SAR) helicopter operations in Arctic areas with limited infrastructure are crucial for saving lives under harsh weather conditions. This study develops a SAR helicopter response model that first identifies all possible paths for a rescue mission using path network optimization, then quantifies the effects of weather on travel time for each route and finally employs discrete-event and Monte Carlo simulation to evaluate the performance of SAR missions. The approach leverages meteorological data to classify favorable, unfavorable, or no-go conditions for SAR helicopter operability, offering insights into travel and rescue times from SAR bases to people in distress across the Canadian Arctic. Preliminary findings highlight how route selection, weather severity, and refueling constraints influence mission durations. While further work is needed to develop, test, and validate the model, these results indicate the model’s promise to enhance SAR planning, reinforcing community resilience under harsh, changing Arctic environments.