An Ant Colony Optimization Memorizing Better Solutions (ACO-MBS) for Traveling Salesman Problem

dc.contributor.authorEkmekci, D.
dc.date.accessioned2024-09-29T16:20:50Z
dc.date.available2024-09-29T16:20:50Z
dc.date.issued2019
dc.departmentKarabük Üniversitesien_US
dc.description3rd International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2019 -- 11 October 2019 through 13 October 2019 -- Ankara -- 156063en_US
dc.description.abstractAnt Colony Optimization (ACO) is a population-based meta-heuristic method that mimics the foraging behavior of the ant colony in real life. The pheromone approach as the highlight method of the algorithm is the most effective factor in determining the moving of ants. Therefore, the problem of tuning the pheromone trail is an important topic for ACO that deserves attention. In this paper, a novel method which memorizes the solution costs and updates the pheromone trail according to the memorized costs is introduced for updating the pheromone trail in ACO. The performance of the proposed method was simulated on the Travelling Salesman Problem (TSP) and compared with the versions of ACO algorithm. © 2019 IEEE.en_US
dc.identifier.doi10.1109/ISMSIT.2019.8932768
dc.identifier.isbn978-172813789-6
dc.identifier.scopus2-s2.0-85077982574en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/ISMSIT.2019.8932768
dc.identifier.urihttps://hdl.handle.net/20.500.14619/9362
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof3rd International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2019 - Proceedingsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectant colony optimizationen_US
dc.subjectpheromone updatingen_US
dc.subjecttraveling salesman problemen_US
dc.titleAn Ant Colony Optimization Memorizing Better Solutions (ACO-MBS) for Traveling Salesman Problemen_US
dc.typeConference Objecten_US

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