A new evolutionary clustering search for a no-wait flow shop problem with set-up times

dc.creatorNagano, Marcelo Seido
dc.creatorSilva, Augusto Almeida da
dc.creatorLorena, Luiz Antonio Nogueira
dc.date.accessioned2013-11-06T15:39:51Z
dc.date.accessioned2018-07-04T16:22:31Z
dc.date.available2013-11-06T15:39:51Z
dc.date.available2018-07-04T16:22:31Z
dc.date.created2013-11-06T15:39:51Z
dc.date.issued2012
dc.identifierENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, OXFORD, v. 25, n. 6, p. 1114-1120, SEP, 2012
dc.identifier0952-1976
dc.identifierhttp://www.producao.usp.br/handle/BDPI/42222
dc.identifier10.1016/j.engappai.2012.05.017
dc.identifierhttp://dx.doi.org/10.1016/j.engappai.2012.05.017
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1635004
dc.description.abstractThis paper addresses the m-machine no-wait flow shop problem where the set-up time of a job is separated from its processing time. The performance measure considered is the total flowtime. A new hybrid metaheuristic Genetic Algorithm-Cluster Search is proposed to solve the scheduling problem. The performance of the proposed method is evaluated and the results are compared with the best method reported in the literature. Experimental tests show superiority of the new method for the test problems set, regarding the solution quality. (c) 2012 Elsevier Ltd. All rights reserved.
dc.languageeng
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD
dc.publisherOXFORD
dc.relationENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
dc.rightsCopyright PERGAMON-ELSEVIER SCIENCE LTD
dc.rightsclosedAccess
dc.subjectSCHEDULING
dc.subjectFLOW SHOP
dc.subjectNO-WAIT
dc.subjectSET-UP TIMES SEPARATED
dc.subjectMETAHEURISTIC
dc.titleA new evolutionary clustering search for a no-wait flow shop problem with set-up times
dc.typeArtículos de revistas


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