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Allocation of Forces, Fires, and Effects Using Genetic Algorithms: Summary
Decisionmaking within the Future Battle Command structure will demand an increasing ability to comprehend and structure information on the battlefield. As the military evolves into a networked force, headquarters and others must collect and utilize information from across the battlefield in a timely...
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creator | Pernin, Christopher G Comanor, Katherine Menthe, Lance Moore, Louis R Andersen, Tim |
description | Decisionmaking within the Future Battle Command structure will demand an increasing ability to comprehend and structure information on the battlefield. As the military evolves into a networked force, headquarters and others must collect and utilize information from across the battlefield in a timely and efficient manner. Decision aids and solution methodologies in constructive simulations must be modified to better show how this information affects decisions. Using information about friendly and enemy forces and the terrain, a RAND-developed model that incorporates a genetic algorithm (1) determines preferred Blue routes around Red forces and (2) allocates forces to these routes. This model is unique in its incorporation of many higher-level intelligence products--including intelligence about Red's location, activity, intent, military capability, intelligence capability, and adaptability--into the planning algorithm. The integration of these products allows the model to produce sophisticated look-ahead representations of enemy forces that are superior to the static representations typically used in planning sessions. The model also features terrain representations that measure impassibility, inhospitableness, and shadowing, allowing planners to transcend scenarios that assume a lack of interesting terrain. |
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title | Allocation of Forces, Fires, and Effects Using Genetic Algorithms: Summary |
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