Major Phillip R. Jenkins, Adjunct Assistant Professor of Operations Research
Publications
PEER-REVIEWED JOURNAL ARTICLES (23)
Long*, C.G., Lunday, B.J., and Jenkins, P.R. (2024). Spatiotemporal Network Vulnerability Identification for the Material Routing Problem: a Bilevel Programming Approach. Military Operations Research Journal (forthcoming).
Caballero, W.N., Cooley*, J.P., Banks, D.L., and Jenkins, P.R. (2024). A Behavioral Approach to Stochastic Bayesian Security Games. Annals of Applied Statistics, 18 (1), 199-223. DOI: https://doi.org/10.1214/23-AOAS1786.
Gelbard*, A.G., Jenkins, P.R., and Robbins, M.J. (2024). Enhancing Military Medical Evacuation Dispatching with Armed Escort Management: Comparing Model-Based Reinforcement Learning Approaches. Journal of Defense Modeling and Simulation (forthcoming). DOI: https://doi.org/10.1177/154851292412297.
Wasilefsky*, D.C., Caballero, W.N., Johnstone, C.A., Jenkins, P.R., Gaw, N.B. (2024). Responsible Machine Learning for United States Air Force Pilot Candidate Selection. Decision Support Systems, 180 (May), 114198. DOI: https://doi.org/10.1016/j.dss.2024.114198.
Frial*, V.B., Jenkins, P.R., Robbins, M.J. (2024). Characterizing military medical evacuation dispatching and delivery policies via a self-exciting spatio-temporal Hawkes process model. Journal of the Operational Research Society, 75 (7), 1239-1260. DOI: https://doi.org/10.1080/01605682.2023.2239884.
Caballero, W.N., Gaw, N.B., Jenkins, P.R., Johnstone, C.A. (2023). Toward Automated Instructor Pilots in Legacy Air Force Systems: Physiology-based Flight Difficulty Classification via Machine Learning. Expert Systems with Applications, 231 (November), 120711. DOI: https://doi.org/10.1016/j.eswa.2023.120711.
Rodriguez*, C.A., Jenkins, P.R., Robbins, M.J. (2023). Solving the Joint Military Medical Evacuation Problem via a Random Forest Approximate Dynamic Programming Approach. Expert Systems with Applications, 221 (July), 119751. DOI: https://doi.org/10.1016/j.eswa.2023.119751.
Rao*, A.P., Jenkins, P.R., Pinson*, R.E., Auxier II, J.D., Shattan, M.B., and Patnaik, A.K. (2023). Machine Learning in Analytical Spectroscopy for Nuclear Diagnostics. Applied Optics, 62 (6), A83-A109. DOI: https://doi.org/10.1364/AO.482533.
Pinson*, R.E., Giminaro, A.V., Dugan, C.L., Jenkins, P.R., and Patnaik, A.K. (2023). LIBS and Raman Spectroscopy in Tandem with Machine Learning for Interrogating Weatherization of Lithium Hydride. Applied Optics, 62 (6), 1528-1536. DOI: https://doi.org/10.1364/AO.482304.
Rao*, A.P, Jenkins, P.R., Auxier II, J.D., Shattan, M.B., and Patnaik, A.K. (2022). Enabling orders of magnitude sensitivity improvement for quantification of Ga in a Ce matrix with a compact Echelle spectrometer. Journal of Analytical Atomic Spectrometry, 37 (10), 1975-1980. DOI: https://doi.or/10.1039/D2JA00179A.
Crumpacker*, J.B, Robbins, M.J., Jenkins, P.R. (2022). An Approximate Dynamic Programming Approach for Solving an Air Combat Maneuvering Problem. Expert Systems with Applications, 203 (October), 117448. DOI: https://doi.org/10.1016/j.eswa.2022.117448.
Rao*, A.P, Jenkins, P.R., Auxier II, J.D., Shattan, M.B., and Patnaik, A.K. (2022). Analytical comparisons of handheld LIBS and XRF devices for rapid quantification of gallium in plutonium surrogate matrix. Journal of Analytical Atomic Spectrometry, 37 (5), 1090-1098. DOI: https://doi.org/10.1039/D1JA00404B.
Rao*, A.P, Jenkins, P.R., Auxier II, J.D., Shattan, M.B., and Patnaik, A.K. (2022). Development of advanced machine learning models for analysis of plutonium surrogate optical emission spectra. Applied Optics, 61 (7), D30-D38. DOI: https://doi.org/10.1364/AO.444093.
Jenkins, P.R., Caballero, W.N., and Hill, R.R. (2022). Predicting Success in United States Air Force Pilot Training using Machine Learning Techniques. Socio-Economic Planning, 79 (February), 101121, 1-14. DOI: https://doi.org/10.1016/j.seps.2021.101121.
Rao*, A.P, Jenkins, P.R., Vu, D.M., Auxier II, J.D., and Shattan, M.B. (2021). Rapid quantitative analysis of trace elements in plutonium alloys using a handheld laser-induced breakdown spectroscopy (LIBS) device coupled with chemometrics and machine learning. Analytical Methods, 13 (30), 3368-3378. (2021 HOT Article Award Winner) DOI: https://doi.org/10.1039/D1AY00826A.
Forrest*, N.C., Hill, R.R., and Jenkins, P.R. (2022). An Air Force Pilot Training Recommendation System using Advanced Analytical Methods. INFORMS Journal on Applied Analytics, 52 (2), 198-209. (2023 INFORMS Military and Security Society Koopman Prize Winner). DOI: https://doi.org/10.1287/inte.2021.1099.
Caballero, W.N., Jenkins, P.R., and Keith, A.J. (2021). Poisoning Finite-Horizon Markov Decision Processes at Design Time. Computers and Operations Research, 129 (May), 1-17. DOI: https://doi.org/10.1016/j.cor.2020.105185.
Rao*, A.P, Jenkins, P.R., Auxier II, J.D., and Shattan, M.B. (2021). Comparison of machine learning techniques to optimize the analysis of plutonium surrogate material via a portable LIBS device. Journal of Analytical Atomic Spectrometry, 36 (2), 399-406. (2021 Department of Energy Innovations in Nuclear Technology Research and Development Award Winner). DOI: https://doi.org/10.1039/D0JA00435A.
Jenkins, P.R., Robbins, M.J., and Lunday, B.J. (2021). Approximate Dynamic Programming for the Military Aeromedical Evacuation Dispatching, Preemption-Rerouting, and Redeployment Problem. European Journal of Operational Research, 290 (1), 132-143. DOI: https://doi.org/10.1016/j.ejor.2020.08.004.
Jenkins, P.R., Robbins, M.J., and Lunday, B.J. (2021). Approximate Dynamic Programming for Military Medical Evacuation Dispatching Policies. INFORMS Journal on Computing, 33 (1), 2-26. DOI: https://doi.org/10.1287/ijoc.2019.0930.
Jenkins, P.R., Lunday, B.J., and Robbins, M.J. (2020). Robust, Multi-Objective Optimization for the Military Medical Evacuation Location-Allocation Problem. Omega, 97 (December), 102088, 1-12. DOI: https://doi.org/10.1016/j.omega.2019.07.004.
Robbins, M.J., Jenkins, P.R., Bastian, N.D., and Lunday, B.J. (2020). Approximate Dynamic Programming for the Aeromedical Dispatching Problem: Value Function Approximation Utilizing Multiple Level Aggregation. Omega, 91 (March), 102020, 1-17. (2018 MORS Richard H. Barchi Prize Winner). DOI: https://doi.org/10.1016/j.omega.2018.12.009.
Jenkins, P.R., Robbins, M.J., and Lunday, B.J. (2018). Examining Military Medical Evacuation Dispatching Policies Utilizing a Markov Decision Process Model of a Controlled Queueing System. Annals of Operations Research, 271 (2), 641-678. DOI: https://doi.org/10.1007/s10479-018-2760-z.
* denotes student author.
REFEREED CONFERENCE PROCEEDINGS (2)
Rao*, A.P, Jenkins, P.R., Patnaik, A.K. (2022). Enabling High-Fidelity Spectroscopic Analysis of Plutonium with Machine Learning. In Proceedings Optical Sensors and Sensing Congress 2022 (AIS, LACSEA, Sensors, ES).
Graves*, E.S., Jenkins, P.R., and Robbins, M.J. (2021). Analyzing the Impact of Triage Classification Errors on Military Medical Evacuation Dispatching Policies. In Proceedings of the 2021 Winter Simulation Conference.
* denotes student author.
REFEREED BOOK CHAPTERS (1)
Jenkins, P.R., Robbins, M.J. (2023). Military and Security Applications: Medical Evacuation. The Encyclopedia of Optimization. DOI: https://doi.org/10.1007/978-3-030-54621-2_760-1.
MONOGRAPHS (2)
Jenkins, P.R. (2019). Strategic Location and Dispatch Management of Assets in a Military Medical Evacuation Enterprise. Ph.D. dissertation, Air Force Institute of Technology.
Jenkins, P.R. (2017). Using Markov Decision Processes with Heterogeneous Queueing Systems to Examine Military MEDEVAC Dispatching Policies. Master’s thesis, Air Force Institute of Technology.
OTHER PUBLICATIONS (5)
Jenkins, P.R., and Weir, J.D. (2023). Enhancing Military Operations through the Integration of Operations Analysis Officers into Air Operations Center Divisions and Air Force Wings. Phalanx, 56 (3), 14-17.
Jenkins, P.R., Robbins, M.J., and Lunday, B.J. (2023). Tutorial -- Transforming a Continuous-Time Markov Decision Process to an Equivalent Discrete-Time Markov Decision Process via Uniformization, with Application to Military Medical Evacuation. Medium, 2023.
Jenkins, P.R., Robbins, M.J., and Lunday, B.J. (2021). Optimising Aerial Military Medical Evacuation Dispatching Decisions via Operations Research Techniques. BMJ Military Health, 169 (e1), e90-e92. DOI: http://dx.doi.org/10.1136/bmjmilitary-2020-001631.
Jenkins, P.R., Lunday, B.J., and Robbins, M.J. (2020). Artificial Intelligence for Medical Evacuation in Great-Power Conflict. War on the Rocks, 2020.
Jenkins, P.R., Lunday, B.J., and Robbins, M.J. (2020). Aerial MEDEVAC Operations Decision-making under Uncertainty to Save Lives. Phalanx, 53 (1), 63-66.
