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Multi-objective Optimal Control of a Pandemic Model for Covid-19 Management

Multi-objective Optimal Control of a Pandemic Model for Covid-19 Management

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GEBERT, Jens, 2022. Multi-objective Optimal Control of a Pandemic Model for Covid-19 Management [Master thesis]. Konstanz: Universität Konstanz

@mastersthesis{Gebert2022Multi-56929, title={Multi-objective Optimal Control of a Pandemic Model for Covid-19 Management}, year={2022}, address={Konstanz}, school={Universität Konstanz}, author={Gebert, Jens} }

<rdf:RDF xmlns:dcterms="http://purl.org/dc/terms/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:void="http://rdfs.org/ns/void#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/rdf/resource/123456789/56929"> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/rdf/resource/123456789/39"/> <dcterms:abstract xml:lang="eng">Decision makers face the need of making difficult decisions with no clear, favorable path on a regular basis. This is illustrated especially impressive since the start of the Covid-19 pandemic in the beginning of 2020. These decisions consist often of different, contradictory objectives. Therefore there is a need for easy and fast applicable tools to find optimal solutions. A possible way to decide multi-objective problems efficiently and scientifically is presented by this work, exemplary on the use of different countermeasures in the pandemic management in Berlin, Germany, in November 2020. First a model of ordinary differential equations (ODE) is introduced to simulate the pandemic proceeding. This model is then run for different countermeasures and a regression with respect to these is made. Consequently it is possible to forecast the pandemic behaviour in dependency of the use of countermeasures. In a second step a variance of the subdivision algorithm is introduced, combining the approaches from [Del04] and [Ser06] as appropriate tool to find optimal solutions for contradictory objectives with respect to the use of countermeasures. This tool is then applied to an exemplary objective function in order to illustrate the use of the subdivision algorithm and how decision making can be based upon its findings. This work is highly influenced by the work of Wulkow et al. [Wul21], as it recreates their work mostly. However, it delivers more mathematical background for the underlying mechanism as well as a more detailed view of how to apply the different tools correctly and can therefore be understood as an extended instruction to apply multiobjective optimization to practical decision making.</dcterms:abstract> <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/56929"/> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2022-03-22T07:17:38Z</dcterms:available> <dc:rights>terms-of-use</dc:rights> <dc:creator>Gebert, Jens</dc:creator> <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/> <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/56929/3/Gebert_2-1o914rtznyx7k5.pdf"/> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/56929/3/Gebert_2-1o914rtznyx7k5.pdf"/> <dc:language>eng</dc:language> <dcterms:issued>2022</dcterms:issued> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2022-03-22T07:17:38Z</dc:date> <dc:contributor>Gebert, Jens</dc:contributor> <dcterms:title>Multi-objective Optimal Control of a Pandemic Model for Covid-19 Management</dcterms:title> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/rdf/resource/123456789/39"/> </rdf:Description> </rdf:RDF>

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