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김영대

Kim, Youngdae
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dc.citation.title OPTIMIZATION LETTERS -
dc.contributor.author Papageorgiou, Dimitri J. -
dc.contributor.author Kronqvist, Jan -
dc.contributor.author Ramanujam, Asha -
dc.contributor.author Kor, James -
dc.contributor.author Kim, Youngdae -
dc.contributor.author Li, Can -
dc.date.accessioned 2024-08-05T15:05:06Z -
dc.date.available 2024-08-05T15:05:06Z -
dc.date.created 2024-08-05 -
dc.date.issued 2024-06 -
dc.description.abstract When faced with a limited budget of function evaluations, state-of-the-art black-box optimization (BBO) solvers struggle to obtain globally, or sometimes even locally, optimal solutions. In such cases, one may pursue solution polishing, i.e., a computational method to improve (or "polish") an incumbent solution, typically via some sort of evolutionary algorithm involving two or more solutions. While solution polishing in "white-box" optimization has existed for years, relatively little has been published regarding its application in costly-to-evaluate BBO. To fill this void, we explore two novel methods for performing solution polishing along one-dimensional curves rather than along straight lines. We introduce a convex quadratic program that can generate promising curves through multiple elite solutions, i.e., via path relinking, or around a single elite solution. In comparing four solution polishing techniques for continuous BBO, we show that solution polishing along a curve is competitive with solution polishing using a state-of-the-art BBO solver. -
dc.identifier.bibliographicCitation OPTIMIZATION LETTERS -
dc.identifier.doi 10.1007/s11590-024-02127-8 -
dc.identifier.issn 1862-4472 -
dc.identifier.scopusid 2-s2.0-85195647370 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/83398 -
dc.identifier.wosid 001244638300001 -
dc.language 영어 -
dc.publisher SPRINGER HEIDELBERG -
dc.title Solution polishing via path relinking for continuous black-box optimization -
dc.type Article -
dc.description.isOpenAccess FALSE -
dc.relation.journalWebOfScienceCategory Operations Research & Management Science; Mathematics, Applied -
dc.relation.journalResearchArea Operations Research & Management Science; Mathematics -
dc.type.docType Article; Early Access -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.subject.keywordAuthor Black-box optimization -
dc.subject.keywordAuthor Derivative-free optimization -
dc.subject.keywordAuthor Line search -
dc.subject.keywordAuthor Path relinking -
dc.subject.keywordAuthor Solution polishing -
dc.subject.keywordPlus DERIVATIVE-FREE OPTIMIZATION -

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