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An optimization approach for the job shop scheduling problem

dc.contributor.authorMagalhães-Mendes, J.
dc.date.accessioned2014-06-12T11:00:32Z
dc.date.available2014-06-12T11:00:32Z
dc.date.issued2009
dc.description.abstractThis paper presents an optimization approach for the job shop scheduling problem (JSSP). The JSSP is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. The proposed approach is based on a genetic algorithm technique. The scheduling rules such as SPT and MWKR are integrated into the process of genetic evolution. The chromosome representation of the problem is based on random keys. The schedules are constructed using a priority rule in which the priorities and delay times of the operations are defined by the genetic algorithm. Schedules are constructed using a procedure that generates parameterized active schedules. After a schedule is obtained a local search heuristic is applied to improve the solution. The approach is tested on a set of standard instances taken from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed approach.por
dc.identifier.doi10.5555/1736344.1736367
dc.identifier.isbn978-960-474-138-0
dc.identifier.urihttp://hdl.handle.net/10400.22/4531
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherWorld Scientific and Engineering Academy and Societypor
dc.relation.ispartofseries14th WSEAS International Conference on Applied Mathematics;
dc.relation.publisherversionhttp://dl.acm.org/citation.cfm?id=1736367por
dc.titleAn optimization approach for the job shop scheduling problempor
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage125por
oaire.citation.startPage120por
oaire.citation.titleMATH'09 Proceedings of the 14th WSEAS International Conference on Applied Mathematicspor
rcaap.rightsopenAccesspor
rcaap.typearticlepor

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