Date of Award
Mathematics, Engineering & Computer Science
Prof. Eric Sullivan
Prof. Philip Rose
Prof. Doug MacKenzie
The cost of wildfires has been climbing drastically. In 2012, the total estimated cost for Montana wildfire suppression was $113.5 million. The goal of this research was to see if it was mathematically possible to minimize wildfire cost while ensuring that a fire is efficiently suppressed. A linear program(LP) was designed to minimize suppression cost while allocating the required hand, air, and equipment crews to specific stages of a wildfire. Two scenarios are implemented into the linear program, where optimal solutions are found. First, a one wildfire scenario is simulated. Secondly, the most extreme fires of Montana's 2012 wildfire season are simulated. Finally, the LP's optimal results, are compared and analyzed with the actual 2012 fire results. Based on the model's outcomes, it was found that dispatch centers with more available equipment, ready to suppress a wildfire, had a lower suppression cost. Although the model manages to meet management requirements, it doesn't account for intangible factors that go into decision making. In conclusion, the linear program provides an optimal solution for wildfire decision management, and under given constraints will efficiently determine the lowest cost while meeting suppression requirements.
King, Joe, "Burning Down the Cost: A Study to Optimize Wildfire Expenses" (2014). Mathematics, Engineering and Computer Science Undergraduate Theses. 15.