A Scatter Search Method for Multiobjective Fuzzy Permutation Flow Shop Scheduling Problem: A Real World Application

dc.contributor.authorEngin, Orhan
dc.contributor.authorKahraman, Cengiz
dc.contributor.authorYılmaz, Mustafa Kerim
dc.date.accessioned2020-03-26T17:37:46Z
dc.date.available2020-03-26T17:37:46Z
dc.date.issued2009
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractIn this chapter, a scatter search (SS) method is proposed to solve the multiobjective permutation fuzzy flow shop scheduling problem. The objectives are minimizing the average tardiness and the number of tardy jobs. The developed scatter search method is tested on real-world data collected at an engine piston manufacturing company. Using the proposed SS algorithm, the best set of parameters is used to obtain the optimal or near optimal solutions of multiobjective fuzzy flow shop scheduling problem in the shortest time. These parameters are determined by full factorial design of experiments (DOE). The feasibility and effectiveness of the proposed scatter search method is demonstrated by comparing it with the hybrid genetic algorithm (HGA).en_US
dc.identifier.endpage189en_US
dc.identifier.isbn978-3-642-02835-9
dc.identifier.issn1860-949Xen_US
dc.identifier.issn1860-9503en_US
dc.identifier.scopusqualityQ4en_US
dc.identifier.startpage169en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/23231
dc.identifier.volume230en_US
dc.identifier.wosWOS:000270008400006en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSPRINGERen_US
dc.relation.ispartofCOMPUTATIONAL INTELLIGENCE IN FLOW SHOP AND JOB SHOP SCHEDULINGen_US
dc.relation.ispartofseriesStudies in Computational Intelligence
dc.relation.publicationcategoryKitap Bölümü - Uluslararasıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.titleA Scatter Search Method for Multiobjective Fuzzy Permutation Flow Shop Scheduling Problem: A Real World Applicationen_US
dc.typeBook Chapteren_US

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