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One dimensional consensus based algorithm for non-convex optimization

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dc.contributor.authorYoung-Pil Choi-
dc.contributor.authorDOWAN KOO-
dc.date.accessioned2023-04-10T01:40:08Z-
dc.date.available2023-04-10T01:40:08Z-
dc.date.issued2022-02-
dc.identifier.issn0893-9659-
dc.identifier.urihttps://yscholarhub.yonsei.ac.kr/handle/2021.sw.yonsei/6336-
dc.description.abstractWe analyze the consensus based optimization method proposed in Pinnau et al. (2017) in one dimension. We rigorously provide a quantitative error estimate between the consensus point and global minimizer of a given objective function. Our analysis covers general objective functions; we do not require any structural assumption on the objective function.-
dc.language영어-
dc.language.isoENG-
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD-
dc.titleOne dimensional consensus based algorithm for non-convex optimization-
dc.typeArticle-
dc.publisher.location영국-
dc.identifier.doi10.1016/j.aml.2021.107658-
dc.identifier.scopusid2-s2.0-85115892963-
dc.identifier.wosid000704350700016-
dc.identifier.bibliographicCitationAPPLIED MATHEMATICS LETTERS, v.124, pp 107658-1 - 107658-8-
dc.citation.titleAPPLIED MATHEMATICS LETTERS-
dc.citation.volume124-
dc.citation.startPage107658-1-
dc.citation.endPage107658-8-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.subject.keywordAuthorConsensus based optimization-
dc.subject.keywordAuthorGradient-free optimization method-
dc.subject.keywordAuthorNon-convex optimization-
dc.subject.keywordAuthorQuantified optimization-
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