Solving power transmission line routing problem using improved genetic and artificial bee colony algorithms

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dc.contributor.authorEroglu, Hasan
dc.contributor.authorAydin, Musa
dc.date.accessioned2020-03-26T19:55:42Z
dc.date.available2020-03-26T19:55:42Z
dc.date.issued2018
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractIn engineering studies, finding the best route from a start point to an end point on pixel-based weighted maps is a big problem for researchers. For this problem many methods and algorithms have been developed until now. The "cost distance" (CD) and "cost path" (CP) tools that are used by a modified Dijkstra's algorithm and used by Environmental Systems Research Institute's (ESRI) ArcGIS Desktop 10 software are very fast and most preferred solutions for route optimization problems. Despite the advantages of these tools, they have the disadvantage of making a lot of curves with big angles. Especially in some engineering studies like power transmission lines' routing, the angle of the curves of the lines should not have big values. For overcoming this problem both genetic algorithm (GA) and artificial bee colony (ABC) algorithm that have been improved and adapted for the problem were used as powerful optimizers to find the best routes with fewer curves in those kinds of optimum route problems. New functions like smart direction sensing and improved random functions were developed for application of GA and ABC algorithms in power transmission lines routing studies. This study showed that the ABC algorithm's performance is better than GA. The accuracy of the algorithms was proven by comparing the results with the CD-CP tools' results. The experimental results showed that the improved algorithms gave better performance than Dijkstra's algorithm.en_US
dc.identifier.doi10.1007/s00202-018-0688-6en_US
dc.identifier.endpage2116en_US
dc.identifier.issn0948-7921en_US
dc.identifier.issn1432-0487en_US
dc.identifier.issue3en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage2103en_US
dc.identifier.urihttps://dx.doi.org/10.1007/s00202-018-0688-6
dc.identifier.urihttps://hdl.handle.net/20.500.12395/36950
dc.identifier.volume100en_US
dc.identifier.wosWOS:000440282300071en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSPRINGERen_US
dc.relation.ispartofELECTRICAL ENGINEERINGen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectOptimum routeen_US
dc.subjectGenetic algorithm (GA)en_US
dc.subjectArtificial bee colony algorithm (ABC)en_US
dc.subjectGeographic information systems (GIS)en_US
dc.subjectPower transmission lines routingen_US
dc.subjectPower transmission planningen_US
dc.titleSolving power transmission line routing problem using improved genetic and artificial bee colony algorithmsen_US
dc.typeArticleen_US

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