Publication:
A Guide for Genetic Algorithm Based on Parallel Machine Scheduling and Flexible Job-Shop Scheduling

dc.contributor.authorAk, Bilgesu
dc.contributor.authorKoc, Erdem
dc.date.accessioned2020-06-21T14:28:16Z
dc.date.available2020-06-21T14:28:16Z
dc.date.issued2012
dc.departmentOMÜen_US
dc.department-temp[Ak, Bilgesu -- Koc, Erdem] Ondokuz Mayis Univ, Dept Ind Engn, TR-55139 Samsun, Turkey --en_US
dc.descriptionWorld Conference on Business, Economics and Management (BEM) -- MAY 04-06, 2012 -- Antalya, TURKEYen_US
dc.description.abstractParallel Machine Scheduling (PMS) and Flexible Job-shop Scheduling (FJS) are the hardest combinatorial optimization problems, they require very large scale search space. Solving this kind of combinatorial optimization problems with classical methods are almost impossible or takes considerable long time. Genetic Algorithms (GAs) have shown great advantages in solving combinatorial problems. GAs have the flexibility of set up different chromosome structures in case of distinctive scheduling problems. This paper presents a PMS and FJS chromosome structure, crossover and mutation operator from literature in order to guide for new researchers about scheduling with GAs. (C) 2012 Published by Elsevier Ltd. Selection and/or peer review under responsibility of Prof. Dr. Huseyin Araslien_US
dc.identifier.doi10.1016/j.sbspro.2012.09.138
dc.identifier.endpage823en_US
dc.identifier.issn1877-0428
dc.identifier.startpage817en_US
dc.identifier.urihttps://doi.org/10.1016/j.sbspro.2012.09.138
dc.identifier.urihttps://hdl.handle.net/20.500.12712/16698
dc.identifier.volume62en_US
dc.identifier.wosWOS:000319841600133
dc.language.isoenen_US
dc.publisherElsevier Science BVen_US
dc.relation.ispartofseriesProcedia Social and Behavioral Sciences
dc.relation.journalWorld Conference on Business, Economics and Management (Bem-2012)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectParallel Machine Schedulingen_US
dc.subjectFlexible Job Shop Problemen_US
dc.subjectGenetic Algorithmen_US
dc.subjectChromosome Representationen_US
dc.subjectCrossover and Mutation Operatorsen_US
dc.titleA Guide for Genetic Algorithm Based on Parallel Machine Scheduling and Flexible Job-Shop Schedulingen_US
dc.typeConference Objecten_US
dspace.entity.typePublication

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