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dc.contributor.authorLi, Zhiyongde
dc.contributor.authorRudolph, Günterde
dc.date.accessioned2009-05-12T16:01:17Z-
dc.date.available2009-05-12T16:01:17Z-
dc.date.issued2007-04de
dc.identifier.urihttp://hdl.handle.net/2003/26135-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-8713-
dc.description.abstractIn this paper, a general framework of quantum-inspired multiobjective evolutionary algorithms is proposed based on the basic principles of quantum computing and general schemes of multi-objective evolutionary algorithms. One of the sufficient convergence conditions to Pareto optimal set is presented and it is proved under partially order set theory. Moreover, two algorithms are given as examples meeting this convergence condition, in which two improved Q-gates are used. Their convergence properties are discussed. Additionally, one counterexample is also given.en
dc.language.isoende
dc.relation.ispartofseriesReihe CI; 228-07de
dc.subjectmulti-objective evolutionary algorithmsen
dc.subjectPareto optimal seten
dc.subjectquantum computingen
dc.subjectstochastic convergenceen
dc.subject.ddc004de
dc.titleA framework of quantum-inspired multi-objective evolutionary algorithms and its convergence propertiesen
dc.typeTextde
dc.type.publicationtypereportde
dcterms.accessRightsopen access-
Appears in Collections:Sonderforschungsbereich (SFB) 531

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