Effectiveness of Genetic Algorithm in the Solution of Multidisciplinary Conference Scheduling Problem

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dc.authorscopusid56557054300
dc.authorscopusid36503422100
dc.contributor.authorAtagün, E.
dc.contributor.authorBiroğul, S.
dc.date.accessioned2021-12-01T18:38:56Z
dc.date.available2021-12-01T18:38:56Z
dc.date.issued2021
dc.department[Belirlenecek]en_US
dc.description.abstractMultidisciplinary conferences are the types of conferences that allow the presentation of studies in different disciplines such as naturel science, social sciences, health and arts sciences etc. In these conferences, determining the days, halls and sessions and making presentations according to the related main-scope and sub-scopes, are an important limited optimization problem. The fact that there are presentations from different disciplines in same session during the conference is a big problem for the conference participants. In this study, the solution of the scheduling problem of multidisciplinary conferences with Genetic Algorithm approach is discussed. The basic concepts of Genetic Algorithm are given and conference scheduling schemes and the elements to be considered in scheduling are indicated. In this study, two different multidisciplinary conference datasets have been used. An application has been developed with Genetic Algorithm in C# language under some constraints of the different days, different sessions and different rooms. As a result of the study, it is seen that the solutions obtained with Genetic Algorithm are generally close to optimum solutions. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.en_US
dc.identifier.doi10.1007/978-3-030-79357-9_22
dc.identifier.endpage230en_US
dc.identifier.issn23674512
dc.identifier.scopus2-s2.0-85109890102en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage220en_US
dc.identifier.urihttps://doi.org/10.1007/978-3-030-79357-9_22
dc.identifier.urihttps://hdl.handle.net/20.500.12684/9924
dc.identifier.volume76en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.relation.ispartofLecture Notes on Data Engineering and Communications Technologiesen_US
dc.relation.publicationcategoryKitap Bölümü - Uluslararasıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectGenetic Algorithmen_US
dc.subjectOptimizationen_US
dc.subjectSchedulingen_US
dc.titleEffectiveness of Genetic Algorithm in the Solution of Multidisciplinary Conference Scheduling Problemen_US
dc.typeBook Chapteren_US

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