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Wildfires are an escalating global threat, and North America is experiencing growing frequency and severity. In Canada alone, more than 8,000 wildfires burn millions of hectares each year — with a record-breaking 18.5 million hectares lost in 2023. This rising crisis places immense pressure on wildfire management agencies to allocate suppression resources effectively and efficiently.

In partnership with the Government of Alberta, we have developed a data-driven framework to optimize wildfire resource deployment. Our approach combines predictive modeling, queuing theory, and robust optimization to forecast daily resource needs, estimate waiting times, and guide real-time allocation decisions. While our case study focuses on Alberta, the methodology is highly adaptable and can support wildfire management strategies across different regions worldwide.