An application of fruit fly optimization algorithm for traveling salesman problem

Basit Öğe Kaydı
dc.contributor.authorIscan, Hazim
dc.contributor.authorGunduz, Mesut
dc.date.accessioned2020-03-26T19:33:45Z
dc.date.available2020-03-26T19:33:45Z
dc.date.issued2017
dc.departmentSelçuk Üniversitesien_US
dc.description8th International Conference on Advances in Information Technology (IAIT) -- DEC 19-22, 2016 -- Macau, PEOPLES R CHINAen_US
dc.description.abstractIn this study, an application of fruit fly optimization algorithm (FOA) is presented. FOA is one of the recently proposed swarm intelligence optimization algorithms used to solve continuous complex optimization problems. FOA has been invented by Pan in 2011 and it is based on the food search behavior of fruit flies. The FOA has a simple framework and it is easy to implement for solving optimization problem with different characteristics. The FOA is also a robust and fast algorithm and some researchers used FOA to solve discrete optimization problems. In this study, a new modified FOA is proposed for solving the well-known traveling salesman problem (TSP) which is one of the most studied discrete optimization problems. In basic FOA, there are two basic phases, one of them is osphresis phase and the other is vision phase. In the modified version of FOA the ospherisis phases kept as it is and for vision phase two different methods developed. In vision phase, the first half of the city arrangement matrix is updated according to first %30 part of best solutions of the ospheresis phase. The other half of the city arrangement matrix is randomly reproduced because of the possibility that initial solutions are far from the optimum. According to the results, travelling salesman problem can be solved with FOA as an alternative method. For big scale problems, it needs some improvements. (c) 2017 The Authors. Published by Elsevier B.V.en_US
dc.description.sponsorshipSelcuk UniversitySelcuk Universityen_US
dc.description.sponsorshipThis study has been supported by Coordinatorship of Scientific Research Projects of Selcuk University.en_US
dc.identifier.doi10.1016/j.procs.2017.06.010en_US
dc.identifier.endpage63en_US
dc.identifier.issn1877-0509en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage58en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.procs.2017.06.010
dc.identifier.urihttps://hdl.handle.net/20.500.12395/34779
dc.identifier.volume111en_US
dc.identifier.wosWOS:000418465800009en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherELSEVIER SCIENCE BVen_US
dc.relation.ispartof8TH INTERNATIONAL CONFERENCE ON ADVANCES IN INFORMATION TECHNOLOGYen_US
dc.relation.ispartofseriesProcedia Computer Science
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectFruit fly optimization algorithmen_US
dc.subjectmetaheuristicen_US
dc.subjectFOAen_US
dc.subjectFFOAen_US
dc.subjecttraveling salesman problemen_US
dc.subjectdiscrete optimization problemen_US
dc.titleAn application of fruit fly optimization algorithm for traveling salesman problemen_US
dc.typeConference Objecten_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu