A discrete artificial bee colony algorithm for single machine scheduling problems

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dc.contributor.buuauthorYurtkuran, Alkin
dc.contributor.buuauthorEmel, Erdal
dc.contributor.departmentUludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü.tr_TR
dc.contributor.orcid0000-0002-9220-7353tr_TR
dc.contributor.orcid0000-0003-2978-2811tr_TR
dc.contributor.researcheridN-8691-2014tr_TR
dc.contributor.researcheridAAH-1410-2021tr_TR
dc.contributor.scopusid26031880400tr_TR
dc.contributor.scopusid6602919521tr_TR
dc.date.accessioned2022-11-21T05:57:53Z
dc.date.available2022-11-21T05:57:53Z
dc.date.issued2016-04-27
dc.description.abstractThis paper presents a discrete artificial bee colony algorithm for a single machine earliness-tardiness scheduling problem. The objective of single machine earliness-tardiness scheduling problems is to find a job sequence that minimises the total sum of earliness-tardiness penalties. Artificial bee colony (ABC) algorithm is a swarm-based meta-heuristic, which mimics the foraging behaviour of honey bee swarms. In this study, several modifications to the original ABC algorithm are proposed for adapting the algorithm to efficiently solve combinatorial optimisation problems like single machine scheduling. In proposed study, instead of using a single search operator to generate neighbour solutions, random selection from an operator pool is employed. Moreover, novel crossover operators are presented and employed with several parent sets with different characteristics to enhance both exploration and exploitation behaviour of the proposed algorithm. The performance of the presented meta-heuristic is evaluated on several benchmark problems in detail and compared with the state-of-the-art algorithms. Computational results indicate that the algorithm can produce better solutions in terms of solution quality, robustness and computational time when compared to other algorithms.en_US
dc.identifier.citationYurtkuran, A. ve Emel, E. (2016). "A discrete artificial bee colony algorithm for single machine scheduling problems". International Journal of Production Research, 54(22), 6860-6878.en_US
dc.identifier.endpage6878tr_TR
dc.identifier.issn0020-7543
dc.identifier.issn1366-588X
dc.identifier.issue22tr_TR
dc.identifier.scopus2-s2.0-84966909167tr_TR
dc.identifier.startpage6860tr_TR
dc.identifier.urihttps://doi.org/10.1080/00207543.2016.1185550
dc.identifier.urihttps://www.tandfonline.com/doi/full/10.1080/00207543.2016.1185550
dc.identifier.urihttp://hdl.handle.net/11452/29496
dc.identifier.volume54tr_TR
dc.identifier.wos000386426300014tr_TR
dc.indexed.scopusScopusen_US
dc.indexed.wosSCIEen_US
dc.language.isoenen_US
dc.publisherTaylor & Francisen_US
dc.relation.journalInternational Journal of Production Researchen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergitr_TR
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectEngineeringen_US
dc.subjectOperations research & management scienceen_US
dc.subjectSchedulingen_US
dc.subjectSingle machineen_US
dc.subjectArtificial bee colony algorithmen_US
dc.subjectMeta-heuristicsen_US
dc.subjectCombinatorial optimisationen_US
dc.subjectJob-shopen_US
dc.subjectBound algorithmen_US
dc.subjectEarlinessen_US
dc.subjectSearchen_US
dc.subjectAlgorithmsen_US
dc.subjectBenchmarkingen_US
dc.subjectCombinatorial mathematicsen_US
dc.subjectCombinatorial optimizationen_US
dc.subjectEvolutionary algorithmsen_US
dc.subjectHeuristic algorithmsen_US
dc.subjectMachineryen_US
dc.subjectProblem solvingen_US
dc.subjectScheduling algorithmsen_US
dc.subjectArtificial bee colony algorithmsen_US
dc.subjectArtificial bee colony algorithms (ABC)en_US
dc.subjectExploration and exploitationen_US
dc.subjectMeta heuristicsen_US
dc.subjectSingle machine scheduling problemsen_US
dc.subjectSingle- machinesen_US
dc.subjectSingle-machine schedulingen_US
dc.subjectState-of-the-art algorithmsen_US
dc.subjectOptimizationen_US
dc.subject.scopusSingle Machine Scheduling; Tardiness; Scheduling Problemen_US
dc.subject.wosEngineering, industrialen_US
dc.subject.wosEngineering, manufacturingen_US
dc.subject.wosOperations research & management scienceen_US
dc.titleA discrete artificial bee colony algorithm for single machine scheduling problemsen_US
dc.typeArticle
dc.wos.quartileQ2en_US
dc.wos.quartileQ1 (Operations research & management science)en_US

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