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https://hdl.handle.net/20.500.13091/843
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DC Field | Value | Language |
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dc.contributor.author | Keskin, K. | - |
dc.contributor.author | Engin, Orhan | - |
dc.date.accessioned | 2021-12-13T10:32:04Z | - |
dc.date.available | 2021-12-13T10:32:04Z | - |
dc.date.issued | 2021 | - |
dc.identifier.issn | 2523-3971 | - |
dc.identifier.uri | https://doi.org/10.1007/s42452-021-04615-3 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.13091/843 | - |
dc.description.abstract | This paper addresses the m-machine no-wait Flow Shop Scheduling with Setup Times (NW-FSSWST). Two performance measures: total flow time and makespan are considered. The objective is to find a sequence that minimizing total flow time (? Cj) and makespan (Cj) simultaneously. A Hybrid Genetic Local and Global Search Algorithm (HGLGSA) is proposed to solve the NW-FSSWST for two performance criteria. The hybrid genetic algorithm is constructed by insert-search and self-repair algorithm with self-repair function. The proposed HGLGSA is tested on 192 benchmark problems of NW-FSSWST in the literature. A full factorial experimental design is made for determined the best parameter sets that improve the performance of the proposed algorithm. The computational results are compared with the benchmark solutions from the literature. The experimental results demonstrate the effectiveness and efficiency of the proposed HGLGSA for solving NW-FSSWST. © 2021, The Author(s). | en_US |
dc.language.iso | en | en_US |
dc.publisher | Springer Nature | en_US |
dc.relation.ispartof | SN Applied Sciences | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Global search | en_US |
dc.subject | Hybrid genetic algorithm | en_US |
dc.subject | Insert-search | en_US |
dc.subject | Local search | en_US |
dc.subject | Makespan | en_US |
dc.subject | No-wait flow shop scheduling | en_US |
dc.subject | Self-repair | en_US |
dc.subject | Total flow time | en_US |
dc.title | A hybrid genetic local and global search algorithm for solving no-wait flow shop problem with bi criteria | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1007/s42452-021-04615-3 | - |
dc.identifier.scopus | 2-s2.0-85105873945 | en_US |
dc.department | Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Endüstri Mühendisliği Bölümü | en_US |
dc.identifier.volume | 3 | en_US |
dc.identifier.issue | 6 | en_US |
dc.identifier.wos | WOS:001028273900001 | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.authorscopusid | 57223432198 | - |
dc.authorscopusid | 55948252100 | - |
dc.identifier.scopusquality | Q2 | - |
item.grantfulltext | open | - |
item.fulltext | With Fulltext | - |
item.languageiso639-1 | en | - |
item.cerifentitytype | Publications | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.openairetype | Article | - |
crisitem.author.dept | 02.09. Department of Industrial Engineering | - |
Appears in Collections: | Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections |
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File | Size | Format | |
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Keskin-Engin2021_Article_AHybridGeneticLocalAndGlobalSe.pdf | 2.55 MB | Adobe PDF | View/Open |
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