OPTIMIZING RESOURCE AUGMENTATION FOR WILDLAND FIRES

During December 2017, the Los Angeles County Fire Department (LACoFD) responded to an unprecedented number of wildland fires spanning thousands of square miles within the county. While most of the fires were successfully contained, several caused widespread catastrophic damage. During red flag (high-risk) days, LACoFD currently uses augmented staffing, either by moving on-duty equipment and personnel, or mobilizing those who are off duty to reduce response time. Operational duty chiefs make these augmentation decisions based on current weather conditions and experience. This thesis develops regression models to estimate the probability and potential burned acreage of wildland fires in each of 21 sub-areas in the county. Then, a budget-constrained optimization model reassigns resources between sub-areas in order to minimize expected population displacement due to wildland fire. A comparison of these automated techniques with those manual decisions made during December 2017 reveals significant improvements to augmented staffing that can be made at a lower cost.Office of Naval Researchhttp://archive.org/details/optimizingresour1094562835Outstanding ThesisEnsign, United States NavyApproved for public release; distribution is unlimited