EpiGenetic Algorithm for Optimization: Application to Mobile Network Frequency Planning

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dc.contributor.authorBiroğul, Serdar
dc.date.accessioned2020-05-01T12:11:54Z
dc.date.available2020-05-01T12:11:54Z
dc.date.issued2016
dc.departmentDÜ, Teknoloji Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.descriptionWOS: 000371252700010en_US
dc.description.abstractGenetic algorithms (GA) has been used as a successful algorithm for many problems. GA has been redesigned with different methods or used in hybrid algorithms to solve different problems and improve solutions. In this study, epigenetic algorithm (EGA) design has been made by adapting epigenetic concepts to the classical GA structure. GA is counted as a heuristic research algorithm, and there is randomness in the function of genetic operators. However, owing to some serious research in medical field, it has been shown that through the epigenetics, randomness of crossover and mutation operators can be defined. With regards to this information in the field of medicine, in this study design of EGA, how epicrossover, epimutation operators, and epigenetic factors are made and how they do work and also how the epigenetic inheritance is possible have been told. Our designed EGA has been applied on base stations' BCCH frequency planning in GSM network that is a constrained optimization problem. Real base station's data have been used in solving the problem. EGA and GA coding have been made by using C# programming. In order to analyze the success of EGA than the classical GA, both algorithms have been used in solving of this problem. Because of this, EGA gave better results in a shorter time and less iteration than classical GA's.en_US
dc.identifier.doi10.1007/s13369-015-1869-5en_US
dc.identifier.endpage896en_US
dc.identifier.issn2193-567X
dc.identifier.issn2191-4281
dc.identifier.issue3en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage883en_US
dc.identifier.urihttps://doi.org/10.1007/s13369-015-1869-5
dc.identifier.urihttps://hdl.handle.net/20.500.12684/6254
dc.identifier.volume41en_US
dc.identifier.wosWOS:000371252700010en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Heidelbergen_US
dc.relation.ispartofArabian Journal For Science And Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectEpigeneticen_US
dc.subjectEpigenetic algorithmen_US
dc.subjectEpicrossoveren_US
dc.subjectEpimutationen_US
dc.subjectEpi-inheritanceen_US
dc.subjectGenetic algorithmen_US
dc.subjectOptimizationen_US
dc.subjectFrequency planningen_US
dc.titleEpiGenetic Algorithm for Optimization: Application to Mobile Network Frequency Planningen_US
dc.typeArticleen_US

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