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dc.contributor.authorMatousek, Radomil
dc.contributor.authorPopela, Pavel
dc.contributor.authorKudela, Jakub
dc.date.accessioned2019-06-26T10:18:08Z
dc.date.available2019-06-26T10:18:08Z
dc.date.issued2017-06-01cs
dc.identifier.citationMendel. 2017 vol. 23, č. 1, s. 73-78. ISSN 1803-3814cs
dc.identifier.issn2571-3701
dc.identifier.issn1803-3814
dc.identifier.urihttp://hdl.handle.net/11012/179201
dc.description.abstractThe goal of this paper is to continue our investigation of the heuristic approaches of solving thestochastic quadratic assignment problem (StoQAP) and provide additional insight into the behavior of di erentformulations that arise through the stochastic nature of the problem. The deterministic Quadratic AssignmentProblem (QAP) belongs to a class of well-known hard combinatorial optimization problems. Working with severalreal-world applications we have found that their QAP parameters can (and should) be considered as stochasticones. Thus, we review the StoQAP as a stochastic program and discuss its suitable deterministic reformulations.The two formulations we are going to investigate include two of the most used risk measures - Value at Risk(VaR) and Conditional Value at Risk (CVaR). The focus is on VaR and CVaR formulations and results of testcomputations for various instances of StoQAP solved by a genetic algorithm, which are presented and discussed.en
dc.formattextcs
dc.format.extent73-78cs
dc.format.mimetypeapplication/pdfen
dc.language.isoencs
dc.publisherInstitute of Automation and Computer Science, Brno University of Technologycs
dc.relation.ispartofMendelcs
dc.relation.urihttps://mendel-journal.org/index.php/mendel/article/view/55cs
dc.subjectquadratic assignment problemen
dc.subjectstochastic quadratic assignment problemen
dc.subjectVaR and CVaR deterministic reformulationsen
dc.subjectgenetic algorithmen
dc.titleHeuristic Approaches to Stochastic Quadratic Assignment Problem: VaR and CVar Casesen
eprints.affiliatedInstitution.facultyFakulta strojního inženýrstvícs
dc.coverage.issue1cs
dc.coverage.volume23cs
dc.identifier.doi10.13164/mendel.2017.1.073en
dc.rights.accessopenAccessen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen


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