Integrated simulation and optimization for wildfire containment

Abstract

Wildfire containment is an important but challenging task. The ability to predict fire spread behavior, optimize a plan for firefighting resource dispatch and evaluate such a plan using several firefighting tactics is essential for supporting decision making for containing wildfires. In this article, we present an integrated framework for wildfire spread simulation, firefighting resource optimization and wildfire suppression simulation. We present a stochastic mixed-integer programming model for initial attack to generate firefighting resource dispatch plans using as input fire spread scenario results from a standard wildfire behavior simulator. A new agent-based discrete event simulation model for fire suppression is used to simulate fire suppression based on dispatch plans from the stochastic optimization model, and in turn provides feedback to the optimization model for revising the dispatch plans if necessary. We report on several experimental results, which demonstrate that different firefighting tactics can lead to significantly different fire suppression results for a given dispatch plan, and simulation of these tactics can provide valuable information for fire managers in selecting dispatch plans from optimization models before actual implementation in the field.

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