Optimizing Prepositioning of Equipment and Personnel for Los Angeles County Fire Department to Fight Wildland Fires
References
- (1973) Information theory and an extension of the maximum likelihood principle. Proc. Second Internat. Sympos. Inform. Theory (Akademiai Kiado, Budapest), 267–281.Google Scholar
- California Public Utilities Commission (CPUC) (2021) Public safety power shutoff (PSPS)/De-energization. Accessed March 24, 2021, https://www.cpuc.ca.gov/psps/.Google Scholar
- (2019) Firefighters’ fateful choices: How the Woolsey fire became an unstoppable monster. Los Angeles Times (January 6), https://www.latimes.com/local/lanow/la-me-woolsey-resources-20190106-htmlstory.html.Google Scholar
- (2003) An integer programming model to optimize resource allocation for wildfire containment. Forest Sci. 49(2):331–335.Google Scholar
- (2016) Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models (Chapman and Hall, New York).Google Scholar
- (2011) Pyomo: Modeling and solving mathematical programs in Python. Math. Program. Comput. 3(3):219–260.Google Scholar
- (2017) Pyomo—Optimization Modeling in Python (Springer, Berlin).Google Scholar
- (2018) Wildland firefighting resource optimization. Unpublished capstone report, Naval Postgraduate School, Monterey, CA.Google Scholar
- IBM (2019) CPLEX optimization studio. Accessed February 15, 2019, https://www.ibm.com/analytics/cplex-optimizer.Google Scholar
- (1968) A drought index for forest fire control. Report, Southeastern Forest Experiment Station, USDA Forest Service, Asheville, NC.Google Scholar
- (1982) Least squares quantization in PCM. IEEE Trans. Inform. Theory 28(2):129–137.Google Scholar
- Los Angeles County Fire Department (LACoFD) (2020) Overview booklet. Accessed June 30, 2020, https://wearelacountyfire.org/file/la_county_fire_overview_booklet_0317.pdf.Google Scholar
- National Fire Protection Association (NFPA) (2019) Fire loss in the United States in 2019. Accessed June 15, 2021, https://www.nfpa.org/News-and-Research/Data-research-and-tools/US-Fire-Problem/Fire-loss-in-the-United-States.Google Scholar
- National Oceanic and Atmospheric Administration (NOAA) (2019) Dead fuel moisture. National Centers for Environmental Information. Accessed May 7, 2019, https://www.ncdc.noaa.gov/monitoring-references/dyk/deadfuelmoisture.Google Scholar
- National Park Service (2019) Burn index. Accessed March 24, 2021, https://www.fs.fed.us/nwacfire/home/terminology.html.Google Scholar
- National Wildfire Coordinating Group (NWCG) (2019) National Wildfire Coordinating Group. Accessed March 24, 2021, https://www.nwcg.gov/.Google Scholar
- PassMark (2020) CPU benchmarks. Accessed March 24, 2021, https://www.cpubenchmark.net/cpu_list.php.Google Scholar
- (1996) Introduction to Wildland Fire, 2nd ed. (John Wiley and Sons, New York).Google Scholar
- (2010) Initial Attack Effectiveness: Wildfire Staffing Study (Montezuma Publishing, San Diego).Google Scholar
- (2009) Python 3 Reference Manual (CreateSpace, Paramount, CA).Google Scholar
- (1972) A mathematical model for predicting fire spread in wildland fuels. Research paper, Intermountain Forest and Range Experiment Station USDA Forest Service, Ogden, UT.Google Scholar
- (2002) Gaining an understanding of the National Fire Danger Rating System. Technical Report PMS-932, National Wildfire Coordinating Group, Boise, ID.Google Scholar
- (2007) A critical assessment of the burning index in Los Angeles County, California. Internat. J. Wildland Fire 16(4):473–483.Google Scholar
- (2019) Optimizing resource augmentation for wildland fires. Unpublished master’s thesis, Naval Postgraduate School, Monterey, CA.Google Scholar
- (2021) A new simulation-optimization model for wildland fire resource pre-positioning. Master’s thesis, Naval Postgraduate School, Monterey, CA. https://calhoun.nps.edu/handle/10945/66715.Google Scholar
- (1925) The use of liability ratings in planning forest fire protection. J. Agriculcture Res. 30(8):693–792.Google Scholar
- (1999) A dynamic programming approach to determining optimal forest wildfire initial attack responses. Presentation, Symposium on Fire Economics, Planning and Policy: Bottom Lines, April 5–9, Pacific Southwest Research Station, USDA Forest Service, San Diego.Google Scholar

