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Multicriterial Optimization Problems with a Random Element and Stochastic Programming
dc.contributor.advisorKaňková, Vlasta
dc.creatorLíkař, Jan
dc.date.accessioned2017-03-17T11:53:12Z
dc.date.available2017-03-17T11:53:12Z
dc.date.issued2006
dc.identifier.urihttp://hdl.handle.net/20.500.11956/3326
dc.description.abstractIn practice we often have to solve optimization problems with several criteria. These problems are called multicriteria optimization problems. Such problems are presented in this thesis. It is important, whether parameters take unknown values at the moment of making decision. If these parameters are random variables, resulting problem is called stochastic multiobjective problem, otherwise it is called deterministic multiobjective problem. We describe how to choose some "good" solutions of deterministic problem. We investigate their relations as well. In the stochastic case we have to convert such problem to deterministic one. We introduce some possibilities how to do it. Then we are able to solve the problem. These concepts are demonstrated using examples. We present a numerical illustration as well (the Portfolio Selection problem).en_US
dc.languageČeštinacs_CZ
dc.language.isocs_CZ
dc.publisherUniverzita Karlova, Matematicko-fyzikální fakultacs_CZ
dc.titleVícekriteriální optimalizační úlohy s náhodným elementem a stochastické programovánícs_CZ
dc.typediplomová prácecs_CZ
dcterms.created2006
dcterms.dateAccepted2006-02-15
dc.description.departmentDepartment of Probability and Mathematical Statisticsen_US
dc.description.departmentKatedra pravděpodobnosti a matematické statistikycs_CZ
dc.description.facultyFaculty of Mathematics and Physicsen_US
dc.description.facultyMatematicko-fyzikální fakultacs_CZ
dc.identifier.repId41429
dc.title.translatedMulticriterial Optimization Problems with a Random Element and Stochastic Programmingen_US
dc.contributor.refereeDupačová, Jitka
dc.identifier.aleph001459198
thesis.degree.nameMgr.
thesis.degree.levelmagisterskécs_CZ
thesis.degree.disciplineProbability, mathematical statistics and econometricsen_US
thesis.degree.disciplinePravděpodobnost, matematická statistika a ekonometriecs_CZ
thesis.degree.programMathematicsen_US
thesis.degree.programMatematikacs_CZ
uk.thesis.typediplomová prácecs_CZ
uk.taxonomy.organization-csMatematicko-fyzikální fakulta::Katedra pravděpodobnosti a matematické statistikycs_CZ
uk.taxonomy.organization-enFaculty of Mathematics and Physics::Department of Probability and Mathematical Statisticsen_US
uk.faculty-name.csMatematicko-fyzikální fakultacs_CZ
uk.faculty-name.enFaculty of Mathematics and Physicsen_US
uk.faculty-abbr.csMFFcs_CZ
uk.degree-discipline.csPravděpodobnost, matematická statistika a ekonometriecs_CZ
uk.degree-discipline.enProbability, mathematical statistics and econometricsen_US
uk.degree-program.csMatematikacs_CZ
uk.degree-program.enMathematicsen_US
thesis.grade.csVelmi dobřecs_CZ
thesis.grade.enVery gooden_US
uk.abstract.enIn practice we often have to solve optimization problems with several criteria. These problems are called multicriteria optimization problems. Such problems are presented in this thesis. It is important, whether parameters take unknown values at the moment of making decision. If these parameters are random variables, resulting problem is called stochastic multiobjective problem, otherwise it is called deterministic multiobjective problem. We describe how to choose some "good" solutions of deterministic problem. We investigate their relations as well. In the stochastic case we have to convert such problem to deterministic one. We introduce some possibilities how to do it. Then we are able to solve the problem. These concepts are demonstrated using examples. We present a numerical illustration as well (the Portfolio Selection problem).en_US
uk.file-availabilityV
uk.publication.placePrahacs_CZ
uk.grantorUniverzita Karlova, Matematicko-fyzikální fakulta, Katedra pravděpodobnosti a matematické statistikycs_CZ
dc.identifier.lisID990014591980106986


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