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Ant Colony Optimization : An Alternative Heuristic for Aerospace Design Applications


Metadata FieldValueLanguage
dc.contributor.advisorHartfield, Roy J.
dc.contributor.advisorThurow, Brian
dc.contributor.advisorShelton, Andrew
dc.contributor.authorKiyak, Zachary
dc.date.accessioned2014-01-09T20:03:15Z
dc.date.available2014-01-09T20:03:15Z
dc.date.issued2014-01-09
dc.identifier.urihttp://hdl.handle.net/10415/3990
dc.description.abstractA modified ant colony optimization (ACO) algorithm is applied to a set of solid-rocket-motor and single-stage solid missile design problems. A local search procedure is also integrated with the algorithm, adding a search intensification ability that compliments the ability of ACO to thoroughly explore a solution space. The goal of this work is to evaluate the effectiveness of the ant colony optimization scheme by comparing its solution output quality with those of other, well-known optimization methods. Performance is based on solution “fitness", or how closely each solution matches a specific set of performance objectives, as well as the number of calls to the objective function that are required in order to reach that solution. Additionally, an important performance criterion is to determine the algorithm’s capabilities of finding, not only a single quality solution to a design problem, but also a diverse set of additional, near-optimal solutions.en_US
dc.rightsEMBARGO_NOT_AUBURNen_US
dc.subjectAerospace Engineeringen_US
dc.titleAnt Colony Optimization : An Alternative Heuristic for Aerospace Design Applicationsen_US
dc.typethesisen_US
dc.embargo.lengthMONTHS_WITHHELD:6en_US
dc.embargo.statusEMBARGOEDen_US
dc.embargo.enddate2014-07-09en_US

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