A hybrid approach for the multi-criteria-based optimization of sequence-dependent setup-based flow shop scheduling

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dc.authorid0000-0002-7919-544Xen_US
dc.contributor.authorYiğit, Fatih
dc.contributor.authorBasilio, Marcio Pereira
dc.contributor.authorPereira, Valdecy
dc.date.accessioned2024-07-25T09:51:38Z
dc.date.available2024-07-25T09:51:38Z
dc.date.issued2024en_US
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Endüstri Mühendisliği Bölümüen_US
dc.description.abstractA key challenge in production management and operational research is the flow shop scheduling problem, characterized by its complexity in manufacturing processes. Traditional models often assume deterministic conditions, overlooking real-world uncertainties like fluctuating demand, variable processing times, and equipment failures, significantly impacting productivity and efficiency. The increasing demand for more adaptive and robust scheduling frameworks that can handle these uncertainties effectively drives the need for research in this area. Existing methods do not adequately capture modern manufacturing environments’ dynamic and unpredictable nature, resulting in inefficiencies and higher operational costs; they do not employ a fuzzy approach to benefit from human intuition. This study successfully demonstrates the application of Hexagonal Type-2 Fuzzy Sets (HT2FS) for the accurate modeling of the importance of jobs, thereby advancing fuzzy logic applications in scheduling problems. Additionally, it employs a novel Multi-Criteria Decision-Making (MCDM) approach employing Proportional Picture Fuzzy AHP (PPF-AHP) for group decision-making in a flow shop scheduling context. The research outlines the methodology involving three stages: group weight assessment through a PPF-AHP for the objectives, weight determination using HT2FS for the jobs, and optimization via Genetic Algorithm (GA), a method that gave us the optimal solution. This study contributes significantly to operational research and production scheduling by proposing a sophisticated, hybrid model that adeptly navigates the complexities of flow shop scheduling. The integration of HT2FS and MCDM techniques, particularly PPF-AHP, offers a novel approach that enhances decision-making accuracy and paves the way for future advancements in manufacturing optimization.en_US
dc.identifier.citationYiğit, F., Basilio, M. P., Pereira, V. (2024). A hybrid approach for the multi-criteria-based optimization of sequence-dependent setup-based flow shop scheduling. Mathematics, 12(13). 10.3390/math12132007en_US
dc.identifier.issn2227-7390
dc.identifier.issue13en_US
dc.identifier.scopus2-s2.0-85198452549
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://hdl.handle.net/20.500.12939/4780
dc.identifier.volume12en_US
dc.identifier.wosWOS:001269176700001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorYiğit, Fatih
dc.language.isoen
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)en_US
dc.relation.ispartofMathematics
dc.relation.isversionof10.3390/math12132007en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectAsymmetric optimizationen_US
dc.subjectFlow shop schedulingen_US
dc.subjectFuzzy systemsen_US
dc.subjectGenetic algorithmen_US
dc.subjectHT2FSen_US
dc.subjectMCDMen_US
dc.subjectPPF-AHPen_US
dc.titleA hybrid approach for the multi-criteria-based optimization of sequence-dependent setup-based flow shop scheduling
dc.typeArticle

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