A new artificial immune system algorithm for multi objective fuzzy flow shop scheduling: A real world application

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dc.contributor.authorKahraman C.
dc.contributor.authorEngin O.
dc.contributor.authorYilmaz M.K.
dc.date.accessioned2020-03-26T17:28:43Z
dc.date.available2020-03-26T17:28:43Z
dc.date.issued2008
dc.departmentSelçuk Üniversitesien_US
dc.descriptionComputational Intelligence in Decision and Control - 8th International FLINS Conference -- 21 September 2008 through 24 September 2008 -- Madrid -- 74936en_US
dc.description.abstractIn this paper a new artificial immune system (AIS) algorithm is proposed to solve multi objective fuzzy flow shop scheduling problem. The objectives are considered to be minimizing the average tardiness and the number of tardy jobs. The developed new AIS algorithm is applied in an engine cylinder liner manufacturing process. The feasibility and effectiveness of the proposed new AIS is demonstrated by comparing with the Genetic algorithm. Computational results demonstrate that the proposed new AIS algorithm is a more effective meta-heuristic for the multi objective, flow shop scheduling problem with fuzzy processing time and due date.en_US
dc.identifier.endpage1092en_US
dc.identifier.isbn981279946X; 9789812799463
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage1087en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/22835
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.relation.ispartofWorld Scientific Proceedings Series on Computer Engineering and Information Science 1; Computational Intelligence in Decision and Control - Proceedings of the 8th International FLINS Conferenceen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.titleA new artificial immune system algorithm for multi objective fuzzy flow shop scheduling: A real world applicationen_US
dc.typeConference Objecten_US

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