dc.creatorMendes, AS
dc.creatorMuller, FM
dc.creatorFranca, PM
dc.creatorMoscato, P
dc.date2002
dc.dateMAR
dc.date2014-11-17T00:32:41Z
dc.date2015-11-26T17:48:09Z
dc.date2014-11-17T00:32:41Z
dc.date2015-11-26T17:48:09Z
dc.date.accessioned2018-03-29T00:30:56Z
dc.date.available2018-03-29T00:30:56Z
dc.identifierProduction Planning & Control. Taylor & Francis Ltd, v. 13, n. 2, n. 143, n. 154, 2002.
dc.identifier0953-7287
dc.identifierWOS:000173497700005
dc.identifier10.1080/09537280110069649
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/56190
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/56190
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/56190
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1288997
dc.descriptionThe aim of this paper is to compare the performance of two meta-heuristic methods proposed to solve the identical parallel machine scheduling problem with sequence dependent setup times. The goal is to minimize the makespan. The first algorithm is a tabu search based heuristic and the second a memetic approach, which combines a population-based method with local search procedures. As benchmarks for small-sized instances, optimal and lower bound values are used provided by a dichotomous search. For larger instances, the comparisons rely on the best known solutions provided by an exhaustive search variant of the tabu procedure.
dc.description13
dc.description2
dc.description143
dc.description154
dc.languageen
dc.publisherTaylor & Francis Ltd
dc.publisherAbingdon
dc.publisherInglaterra
dc.relationProduction Planning & Control
dc.relationProd. Plan. Control
dc.rightsfechado
dc.rightshttp://journalauthors.tandf.co.uk/permissions/reusingOwnWork.asp
dc.sourceWeb of Science
dc.subjectmachine scheduling
dc.subjectparallel machines
dc.subjectmeta-heuristics
dc.subjecttabu search
dc.subjectmemetic algorithms
dc.titleComparing meta-heuristic approaches for parallel machine scheduling problems
dc.typeArtículos de revistas


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