1. Açık Erişim@BUU
  2. İndeksli Yayınlar
  3. Web of Science
Please use this identifier to cite or link to this item: http://hdl.handle.net/11452/34617
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dc.contributor.authorLirkov, I.-
dc.contributor.authorMargenov, S.-
dc.contributor.authorWasniewski, J.-
dc.date.accessioned2023-10-27T08:10:30Z-
dc.date.available2023-10-27T08:10:30Z-
dc.date.issued2006-
dc.identifier.citationÖzalp, S. A. (2006). ''A genetic algorithm for scheduling of jobs on lines of press machines''. ed. İ. Lirkov, S. Margenov, J. Wasniewski. Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence, 3743, 535-543.en_US
dc.identifier.isbn3-540-31994-8-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://doi.org/10.1007/11666806_61-
dc.identifier.urihttps://link.springer.com/chapter/10.1007%2F11666806_61-
dc.identifier.urihttp://hdl.handle.net/11452/34617-
dc.descriptionBu çalışma, 06-10, Haziran 2005 tarihlerinde Sozopol[Bulgaristan]’da düzenlenen 5. International Conference on Large-Scale Scientific Computing (LSSC 2005) Kongresi‘nde bildiri olarak sunulmuştur.tr_TR
dc.description.abstractThis paper introduces a Genetic Algorithm (GA) based solution technique for press machines scheduling problem of a car manufacturing factory. Firstly, the problem at hand, and the application of the CA in terms of coding, chromosome evaluation, crossover and Mutation operators, are described in detail. After that, the CA is experimentally evaluated through some test problems. As the objective of the problem is the minimization of the completion time of the jobs, the CA based solution is compared with the Longest Processing Time (LPT) rule, and it is observed that the CA always produces better schedules than the LPT rule in a reasonably short amount of CPU time.en_US
dc.description.sponsorshipBulgarian Acad Sci, Inst Parallel Procen_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectComputer scienceen_US
dc.subjectParallel machinesen_US
dc.subjectSchedulingen_US
dc.subjectProgram processorsen_US
dc.subjectProblem solvingen_US
dc.subjectMutagensen_US
dc.subjectChromosomesen_US
dc.subjectPress machinesen_US
dc.subjectLongest processing time (LPT) ruleen_US
dc.subjectChromosome evaluationen_US
dc.subjectGenetic algorithmsen_US
dc.titleA genetic algorithm for scheduling of jobs on lines of press machinesen_US
dc.typeArticleen_US
dc.typeProceedings Paperen_US
dc.identifier.wos000236456400061tr_TR
dc.identifier.scopus2-s2.0-33745323220tr_TR
dc.relation.publicationcategoryKonferans Öğesi - Uluslararasıtr_TR
dc.contributor.departmentUludağ Üniversitesi/Mühendislik Mimarlık Fakültesi/Endüstri Mühendisliği Bölümü.tr_TR
dc.contributor.orcid0000-0001-9201-6349tr_TR
dc.identifier.startpage535tr_TR
dc.identifier.endpage543tr_TR
dc.identifier.volume3743tr_TR
dc.relation.journalLecture Notes in Computer Science, Lecture Notes in Artificial Intelligenceen_US
dc.contributor.buuauthorÖzalp, Selma Ayşe-
dc.contributor.researcheridG-1584-2018tr_TR
dc.contributor.researcheridI-9828-2018tr_TR
dc.subject.wosComputer science, theory & methodsen_US
dc.indexed.wosCPCISen_US
dc.indexed.wosSCIEen_US
dc.indexed.scopusScopusen_US
dc.contributor.scopusid6603978393tr_TR
dc.subject.scopusCommissioning; Virtual Manufacturing; Simulationen_US
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Web of Science

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