A Pheromonal Artificial Bee Colony -pABC-Algorithm for Optimization Problems

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dc.contributor.authorEkmekci, D.
dc.date.accessioned2024-09-29T16:16:39Z
dc.date.available2024-09-29T16:16:39Z
dc.date.issued2019
dc.departmentKarabük Üniversitesien_US
dc.description16th International Multi-Conference on Systems, Signals and Devices, SSD 2019 -- 21 March 2019 through 24 March 2019 -- Istanbul -- 154292en_US
dc.description.abstractArtificial Bee Colony (ABC) algorithm can be used for all kinds of optimization problems for which metaheuristic methods can be used, and it is observed to yield successful results in many applications for different kinds of optimization problems. Ant Colony Optimization (ACO) can successfully evaluate the correlations between solution parts through pheromone approach and ABC algorithm can spread across different regions of the solution space in searching process. In this study, a new hybrid method, developed to improve ABC's performance in terms of local search with pheromone method, is introduced. Proposed method is tested a set of benchmark problems. © 2019 IEEE.en_US
dc.identifier.doi10.1109/SSD.2019.8893259
dc.identifier.endpage456en_US
dc.identifier.isbn978-172811820-8
dc.identifier.scopus2-s2.0-85075632340en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage452en_US
dc.identifier.urihttps://doi.org/10.1109/SSD.2019.8893259
dc.identifier.urihttps://hdl.handle.net/20.500.14619/9251
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof16th International Multi-Conference on Systems, Signals and Devices, SSD 2019en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectartificial bee colonyen_US
dc.subjectoptimizationen_US
dc.subjectswarm intelligenceen_US
dc.titleA Pheromonal Artificial Bee Colony -pABC-Algorithm for Optimization Problemsen_US
dc.typeConference Objecten_US

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