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Optimization case study: ISR allocation in the Global Force Management process

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Author
Carrillo, Guillermo I.
Date
2016-09
Advisor
Owen, Walter E.
Ewing, Paul
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Abstract
Global Force Management (GFM) is a force-allocation process-driven system that distributes military forces across the globe to meet Combatant Commander objectives. The goal is to match military capabilities provided by the military services to Geographic Combatant Commander requirements. This thesis is a proof of concept for an optimization model that maximizes the distribution of a finite number of full motion video intelligence, surveillance, and reconnaissance (ISR) assets to a prioritized list of requirements to meet national security objectives. This thesis examines the ISR GFM process. With the insight gained to the process, the model applies a mixed integer linear programming formulation to provide an optimized force allocation recommendation The model's objective function managed the trade-off between FADM priority and platform consideration, which optimized the allocation 902 hours per day of full motion video to meet 1902 hours per day of 20 CCDR requirements. The research, methodology, and analyses presented in this thesis is a successful proof of concept proving that this optimization model will objectively inform senior decision makers in the Department of Defense for intelligence surveillance reconnaissance Global Force Management allocation.
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This 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.
URI
http://hdl.handle.net/10945/50517
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  • 1. Thesis and Dissertation Collection, all items

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