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dc.contributor.authorAdams, David Bruceen_US
dc.date.accessioned2014-03-14T20:15:06Z
dc.date.available2014-03-14T20:15:06Z
dc.date.issued2005-07-20en_US
dc.identifier.otheretd-08122005-135419en_US
dc.identifier.urihttp://hdl.handle.net/10919/28631
dc.description.abstractComposite panel structure optimization is commonly decomposed into panel optimization subproblems, with specied local loads, resulting in manufacturing incompatibilities between adjacent panel designs. Using genetic algorithms to optimize local panel stacking sequences allows panel populations of stacking sequences to evolve in parallel and send migrants to adjacent panels, so as to blend the local panel designs globally. The blending process is accomplished using the edit distance between individuals of a population and the set of migrants from adjacent panels. The objective function evaluating the tness of designs is modied according to the severity of mismatches detected between neighboring populations. This lays the ground work for natural evolution to a blended global solution without leaving the paradigm of genetic algorithms. An additional method applied here for constructing globally blended panel designs uses a parallel decomposition antithetical to that of earlier work. Rather than performing concurrent panel genetic optimizations, a single genetic optimization is conducted for the entire structure with the parallelism solely within the tness evaluations. A guide based genetic algorithm approach is introduced to exclusively generate and evaluate valid globally blended designs, utilizing a simple masterslave parallel implementation, implicitly reducing the size of the problem design space and increasing the quality of discovered local optima.en_US
dc.publisherVirginia Techen_US
dc.relation.haspartbackup.tar.gzen_US
dc.relation.haspartthesis.pdfen_US
dc.rightsI hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Virginia Tech or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.en_US
dc.subjectBlendingen_US
dc.subjectDecompositionen_US
dc.subjectGenetic Algorithmsen_US
dc.subjectComposite Laminatesen_US
dc.subjectCombinatorial Optimizationen_US
dc.subjectParallel Computingen_US
dc.titleOptimization Frameworks for Discrete Composite Laminate Stacking Sequencesen_US
dc.typeDissertationen_US
dc.contributor.departmentComputer Scienceen_US
dc.description.degreePh. D.en_US
thesis.degree.namePh. D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineComputer Scienceen_US
dc.contributor.committeechairWatson, Layne T.en_US
dc.contributor.committeememberRibbens, Calvin J.en_US
dc.contributor.committeememberAnderson-Cook, Christine M.en_US
dc.contributor.committeememberHeath, Lenwood S.en_US
dc.contributor.committeememberGürdal, Zaferen_US
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-08122005-135419/en_US
dc.date.sdate2005-08-12en_US
dc.date.rdate2005-08-23
dc.date.adate2005-08-23en_US


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