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dc.contributor.advisorDell, Robert F.
dc.contributor.advisorHouse, Jeffrey
dc.contributor.authorSmith, Anthony D.
dc.dateJun-17
dc.date.accessioned2017-08-14T16:46:42Z
dc.date.available2017-08-14T16:46:42Z
dc.date.issued2017-06
dc.identifier.urihttp://hdl.handle.net/10945/55538
dc.descriptionApproved for public release; distribution is unlimiteden_US
dc.description.abstractThe 75th Ranger Regiment is a US Army Special Operations unit responsible for executing raids and forcible entry missions across the globe within 18 hours of notification. In this thesis, we conduct the first data analysis and optimization of Ranger Assessment and Selection Program 1 (RASP1). RASP1 is an eight-week selection for volunteers in the grade of E1 (Private) to E5 (Sergeant) implemented up to ten times per year. We create logistic regression and partition tree models to identify significant factors that contribute to a candidate's success at RASP1 and predict graduation rates. We use an integer linear program (ILP) to prescribe the number of soldiers by grade and Military Occupational Specialty to bring to each RASP1 class to efficiently fill required billets across all units in the Ranger Regiment. We provide the Ranger Regiment leadership with flexible models that offer insight to support their manning decisions. We show effects on RASP1 class composition with changes to capacity constraints, input parameters, and demand. For example, we find the Ranger Regiment could reduce the number of annual RASP1 classes from ten to eight based on several realistic assumptions. Such an annual reduction could save hundreds of man hours and significantly reduce training resource requirements (e.g., ammunition, land use, barracks and food). We encourage detailed exploration of our underlying assumptions and continued use of the ILP.en_US
dc.description.urihttp://archive.org/details/predictingranger1094555538
dc.publisherMonterey, California: Naval Postgraduate Schoolen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titlePredicting Ranger Assessment and Selection Program 1 success and optimizing class compositionen_US
dc.typeThesisen_US
dc.contributor.secondreaderButtrey, Samuel
dc.contributor.departmentOperations Research (OR)
dc.subject.author75th Ranger Regimenten_US
dc.subject.authorSpecial Operationsen_US
dc.subject.authordata analysisen_US
dc.subject.authorinteger linear programmingen_US
dc.subject.authoroptimizationen_US
dc.subject.authorman power analysisen_US
dc.description.serviceMajor, United States Armyen_US
etd.thesisdegree.nameMaster of Science in Operations Researchen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineOperations Researchen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US


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