Pre-emptive and Reactive Resource Allocation in Emergency Response

Emergency response departments face significant challenges due to resource scarcity and fluctuating incident demands. Traditional static resource allocation, assigning resources to fixed stations, often results in inefficiencies, leaving resources underutilized or insufficient in high-demand areas. To address these shortcomings, this research develops a dynamic resource allocation framework tailored specifically for fire departments. The framework integrates preemptive strategies based on historical data and predictive modeling with reactive strategies responding to real-time emergencies. Validated through a case study in Fredericton, Canada, using data from 2017 to 2021, results demonstrate that dynamic allocation significantly reduces response times and enhances resource efficiency compared to static methods. This study provides a data-driven, practical approach to optimizing resource management in fire departments, effectively addressing operational constraints such as geographic challenges, varying demands, and limited resource availability, thereby improving efficiency, readiness, and effectiveness in emergency response operations.