Malatya Public Transportation Route Optimization via Ant Colony Algorithm

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dc.authoridOztemiz, Furkan/0000-0001-5425-3474
dc.authorwosidYeroglu, Celaleddin/ABG-9572-2020
dc.authorwosidOztemiz, Furkan/KOD-2246-2024
dc.contributor.authorOztemiz, Furkan
dc.contributor.authorYeroglu, Celaleddin
dc.date.accessioned2024-08-04T20:45:50Z
dc.date.available2024-08-04T20:45:50Z
dc.date.issued2018
dc.departmentİnönü Üniversitesien_US
dc.descriptionInternational Conference on Artificial Intelligence and Data Processing (IDAP) -- SEP 28-30, 2018 -- Inonu Univ, Malatya, TURKEYen_US
dc.description.abstractIncreasing population density causes traffic densities in city centers. In this study, Ant Colony Algorithm (ACO) was used to find solutions to the traffic problems in crowded cities and Malatya province was chosen as the application region. Need of reducing the traffic intensity in the city centers, has led to the idea that the central stop of public transportation vehicles should be moved. This situation reveals the problem of changing the routes of public transport. In this study, ACO algorithm was used to analyze the new routes in the most ideal way. It is aimed to realize minimum distance and minimum traffic density by solving this problem which is similar to the traveling salesman problem. In order to achieve minimum traffic intensity, the threshold pheromone amount is determined to direct multiple vehicles to alternative routes. The data used in the analysis belongs to the public transportation vehicles of the city of Malatya. A java based program was used to construct the datasets and to solve the problem.en_US
dc.description.sponsorshipInonu Univ, Comp Sci Dept,IEEE Turkey Sect,Anatolian Scien_US
dc.identifier.isbn978-1-5386-6878-8
dc.identifier.scopus2-s2.0-85062568010en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://hdl.handle.net/11616/98708
dc.identifier.wosWOS:000458717400122en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.publisherIeeeen_US
dc.relation.ispartof2018 International Conference on Artificial Intelligence and Data Processing (Idap)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAnt Colony Algorithmen_US
dc.subjectOptimization Algorithmsen_US
dc.subjectTravelling Seller Problemen_US
dc.titleMalatya Public Transportation Route Optimization via Ant Colony Algorithmen_US
dc.typeConference Objecten_US

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