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Preliminary Design of an Autonomous Underwater Vehicle Using a Multiple-Objective Genetic Optimizer

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dc.contributor.authorMartz, Matthewen
dc.contributor.committeechairNeu, Wayne L.en
dc.contributor.committeememberStilwell, Daniel J.en
dc.contributor.committeememberBrown, Alan J.en
dc.contributor.departmentAerospace and Ocean Engineeringen
dc.date.accessioned2014-03-14T20:38:48Zen
dc.date.adate2008-06-26en
dc.date.available2014-03-14T20:38:48Zen
dc.date.issued2008-05-27en
dc.date.rdate2008-06-26en
dc.date.sdate2008-05-27en
dc.description.abstractThe process developed herein uses a Multiple Objective Genetic Optimization (MOGO) algorithm. The optimization is implemented in ModelCenter (MC) from Phoenix Integration. It uses a genetic algorithm that searches the design space for optimal, feasible designs by considering three Measures of Performance (MOPs): Cost, Effectiveness, and Risk. The complete synthesis model is comprised of an input module, the three primary AUV synthesis modules, a constraint module, three objective modules, and a genetic algorithm. The effectiveness rating determined by the synthesis model is based on nine attributes identified in the US Navy's UUV Master Plan and four performance-based attributes calculated by the synthesis model. To solve multi-attribute decision problems the Analytical Hierarchy Process (AHP) is used. Once the MOGO has generated a final generation of optimal, feasible designs the decision-maker(s) can choose candidate designs for further analysis. A sample AUV Synthesis was performed and five candidate AUVs were analyzed.en
dc.description.degreeMaster of Scienceen
dc.identifier.otheretd-05272008-153619en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-05272008-153619/en
dc.identifier.urihttp://hdl.handle.net/10919/33291en
dc.publisherVirginia Techen
dc.relation.haspartMartzThesisRev1.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectMDOen
dc.subjectOptimizationen
dc.subjectGeneticen
dc.subjectGenetic Algorithmen
dc.subjectAUVen
dc.subjectAutonomous Underwater Vehicleen
dc.titlePreliminary Design of an Autonomous Underwater Vehicle Using a Multiple-Objective Genetic Optimizeren
dc.typeThesisen
thesis.degree.disciplineAerospace and Ocean Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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