Efficient path planning for drilling processes: The hybrid approach of a genetic algorithm and ant colony optimisation

dc.authorid0000-0002-1723-4108
dc.authorid0000-0002-7672-1846
dc.contributor.authorTanrıver, Kürşat
dc.contributor.authorAy, Mustafa
dc.date.accessioned2024-08-02T12:53:51Z
dc.date.available2024-08-02T12:53:51Z
dc.date.issued2024
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Mekatronik Mühendisliği Bölümü
dc.description.abstractEfficiency in machining time during drilling is affected by various factors, with one key element being the machining path. Solving the machining path closely resembles the Travelling Salesman Problem (TSP). In this article, drilling on a sample model is simulated using a hybrid algorithm that is developed based on TSP. This hybrid algorithm (GACO) is created by combining the strengths of the Genetic Algorithm (GA) and Ant Colony Optimisation (ACO). Codes written to verify the stability of the algorithms were executed 10 times, and results were recorded indicating the shortest path and machining sequence. Accordingly, the performance of the hybrid GACO algorithm was observed to be 3.16% better than the ACO algorithm in terms of both total path length and total machining time. In terms of computation time, the ACO algorithm lagged behind the GACO algorithm by 6.46%. Furthermore, the hybrid GACO algorithm demonstrated enhanced performance in both total path length and total machining time when compared with the literature. This study aims to contribute to the industry, professionals, and practitioners in this field by providing cost and time savings.
dc.identifier.citationTanrıver, K., & Ay, M. (2024). Efficient path planning for drilling processes: The hybrid approach of a genetic algorithm and ant colony optimisation. Transactions of FAMENA, 48(3), pp. 125-140. https://doi.org/10.21278/TOF.483062023
dc.identifier.doi10.21278/TOF.483062023
dc.identifier.endpage140
dc.identifier.issn1333-1124
dc.identifier.issn1849-1391
dc.identifier.issue3
dc.identifier.scopus2-s2.0-85202545252
dc.identifier.startpage125
dc.identifier.urihttps://doi.org/10.21278/TOF.483062023
dc.identifier.urihttps://hdl.handle.net/20.500.13055/743
dc.identifier.volume48
dc.identifier.wosWOS:001276184900001en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopus
dc.indekslendigikaynak.otherSCI-E - Science Citation Index Expandeden_US
dc.institutionauthorTanrıver, Kürşat
dc.institutionauthorid0000-0002-1723-4108
dc.language.isoen
dc.publisherUniversity of Zagreb
dc.relation.ispartofTransactions of FAMENA
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectAnt Colony
dc.subjectDrilling
dc.subjectTool Pathing Optimisation
dc.subjectTravelling Salesman Person
dc.titleEfficient path planning for drilling processes: The hybrid approach of a genetic algorithm and ant colony optimisation
dc.typeArticle
dspace.entity.typePublication

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