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POD-Based Multiobjective Optimal Control of Time-Variant Heat Phenomena

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BANHOLZER, Stefan, Eugen MAKAROV, Stefan VOLKWEIN, 2017. POD-Based Multiobjective Optimal Control of Time-Variant Heat Phenomena

@techreport{Banholzer2017PODBa-40769, series={Konstanzer Schriften in Mathematik}, title={POD-Based Multiobjective Optimal Control of Time-Variant Heat Phenomena}, year={2017}, number={370}, author={Banholzer, Stefan and Makarov, Eugen and Volkwein, Stefan} }

<rdf:RDF xmlns:dcterms="" xmlns:dc="" xmlns:rdf="" xmlns:bibo="" xmlns:dspace="" xmlns:foaf="" xmlns:void="" xmlns:xsd="" > <rdf:Description rdf:about=""> <dcterms:title>POD-Based Multiobjective Optimal Control of Time-Variant Heat Phenomena</dcterms:title> <dc:creator>Makarov, Eugen</dc:creator> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dc:date rdf:datatype="">2017-11-28T17:14:24Z</dc:date> <dspace:hasBitstream rdf:resource=""/> <dc:creator>Volkwein, Stefan</dc:creator> <dc:creator>Banholzer, Stefan</dc:creator> <dc:rights>terms-of-use</dc:rights> <dspace:isPartOfCollection rdf:resource=""/> <dcterms:rights rdf:resource=""/> <bibo:uri rdf:resource=""/> <dc:language>eng</dc:language> <dcterms:hasPart rdf:resource=""/> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dc:contributor>Makarov, Eugen</dc:contributor> <dcterms:issued>2017</dcterms:issued> <dc:contributor>Volkwein, Stefan</dc:contributor> <dcterms:available rdf:datatype="">2017-11-28T17:14:24Z</dcterms:available> <dc:contributor>Banholzer, Stefan</dc:contributor> <dcterms:abstract xml:lang="eng">In the present paper, a multiobjective optimal control problem governed by a heat equation with time-dependent convection term and bilateral control constraints is considered. For computing Pareto optimal points and approximating the Pareto front, the reference point method is applied. As this method transforms the multiobjective optimal control problem into a series of scalar optimization problems, the method of proper orthogonal decomposition (POD) is introduced as an approach for model-order reduction. New strategies for efficiently updating the POD basis in the optimization process are proposed and tested numerically.</dcterms:abstract> <dcterms:isPartOf rdf:resource=""/> </rdf:Description> </rdf:RDF>

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