Artificial bee colony algorithm including some components of iterated greedy algorithm for permutation flow shop scheduling problems

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dc.authoridArik, Oguzhan Ahmet/0000-0002-7088-2104
dc.contributor.authorArık, Oğuzhan Ahmet
dc.date.accessioned2025-02-24T17:18:55Z
dc.date.available2025-02-24T17:18:55Z
dc.date.issued2021
dc.departmentFakülteler, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü
dc.description.abstractThe permutation flow shop scheduling problem has been investigated by researchers for more than 40 years due to its complexity and lots of real-life examples of the problem. Many exact or approximate solution approaches have been presented for the problem. Among solution approaches in the literature, iterated greedy algorithm and its variants are the most effective solution methods for the problem. This paper proposes a hybrid solution algorithm that uses the best components such as local search operators and destruction/construction operators of the variants of iterated greedy algorithm in an artificial bee colony algorithm. An ANOVA is made for determining the most proper components of iterated greedy algorithm. Then, these components are combined with artificial bee colony algorithm. Furthermore, a design of experiment is made for determining the best parameter setting for the proposed hybrid artificial bee colony. The experimental results of the proposed algorithm compared with variants of iterated greedy algorithms in the literature show that the proposed algorithm produces better solutions that deviate less from the optimum or lower-bound solutions for permutation flow shop scheduling problems with the makespan performance criterion.
dc.identifier.doi10.1007/s00521-020-05174-1
dc.identifier.endpage3486
dc.identifier.issn0941-0643
dc.identifier.issn1433-3058
dc.identifier.issue8
dc.identifier.scopus2-s2.0-85088631332
dc.identifier.scopusqualityQ1
dc.identifier.startpage3469
dc.identifier.urihttps://doi.org/10.1007/s00521-020-05174-1
dc.identifier.urihttps://hdl.handle.net/20.500.14440/914
dc.identifier.volume33
dc.identifier.wosWOS:000553442800001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorArik, Oguzhan Ahmet
dc.language.isoen
dc.publisherSpringer London Ltd
dc.relation.ispartofNeural Computing & Applications
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250201
dc.subjectArtificial bee colony
dc.subjectIterated greedy
dc.subjectPermutation flow shop
dc.subjectMakespan
dc.titleArtificial bee colony algorithm including some components of iterated greedy algorithm for permutation flow shop scheduling problems
dc.typeArticle

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