Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/8811
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dc.contributor.authorAcikalin U.U.-
dc.contributor.authorCaskurlu B.-
dc.date.accessioned2022-11-30T19:20:50Z-
dc.date.available2022-11-30T19:20:50Z-
dc.date.issued2022-
dc.identifier.isbn9.78145E+12-
dc.identifier.urihttps://doi.org/10.1145/3520304.3529050-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/8811-
dc.descriptionACM SIGEVOen_US
dc.description2022 Genetic and Evolutionary Computation Conference, GECCO 2022 -- 9 July 2022 through 13 July 2022 -- -- 181031en_US
dc.description.abstractThe Hypergraph Partitioning (HGP) problem is a well-studied problem that finds applications in a variety of domains. In several application domains, such as the VLSI design and database migration planning, the quality of the solution is more of a concern than the running time of the algorithm. In this work, we introduce novel problem-specific recombination and mutation operators and develop a new multilevel memetic algorithm by combining these operators with kKaHyPar-E. The performance of our algorithm is compared with the state-of-the-art HGP algorithms on 150 real-life instances taken from the benchmark sets used in the literature. The experiments reveal that our algorithm outperforms all others, and finds the best solutions in 112, 115, and 125 instances in 2, 4, and 8 hours, respectively. © 2022 Owner/Author.en_US
dc.language.isoenen_US
dc.publisherAssociation for Computing Machinery, Incen_US
dc.relation.ispartofGECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conferenceen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectmemetic algorithmsen_US
dc.subjectmultilevel hypergraph partitioningen_US
dc.subjectGenetic algorithmsen_US
dc.subjectApplications domainsen_US
dc.subjectDatabase migrationsen_US
dc.subjectHypergraph partitioningen_US
dc.subjectMemeticen_US
dc.subjectMemetic algorithmsen_US
dc.subjectMigration planningen_US
dc.subjectMultilevel hypergraph partitioningen_US
dc.subjectMultilevelsen_US
dc.subjectPartitioning problemen_US
dc.subjectVLSI designen_US
dc.subjectBenchmarkingen_US
dc.titleMultilevel Memetic Hypergraph Partitioning With Greedy Recombinationen_US
dc.typeConference Objecten_US
dc.identifier.startpage168en_US
dc.identifier.endpage171en_US
dc.identifier.wosWOS:001035469400062en_US
dc.identifier.scopus2-s2.0-85136331557en_US
dc.identifier.doi10.1145/3520304.3529050-
dc.authorscopusid35309348400-
dc.authorscopusid35104543000-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.ozel2022v3_Editen_US
item.openairetypeConference Object-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
crisitem.author.dept02.1. Department of Artificial Intelligence Engineering-
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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