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Conference Paper: Heuristics and genetic algorithms for minimizing makespan of assembly jobs

TitleHeuristics and genetic algorithms for minimizing makespan of assembly jobs
Authors
Lu, HHuang, GQDai, Q
KeywordsAssembly Job Shop
Backward Scheduling
Forward Scheduling
Genetic Algorithm
Heuristics
Issue Date2010
Citation
40Th International Conference On Computers And Industrial Engineering: Soft Computing Techniques For Advanced Manufacturing And Service Systems, Cie40 2010, 2010 How to Cite?
DOI: http://dx.doi.org/10.1109/ICCIE.2010.5668255
AbstractAssembly jobs can be seen as a more generalized version of traditional jobs. A traditional job refers to one with only sequential operations while an assembly job refers to one with additional assembly operations and complex product structures. This research proposes and compares genetic algorithms and heuristics for scheduling assembly jobs. The objective is to minimize the makespan (maximum completion time) of a given set of assembly jobs. Experiments have been conducted to compare the performance of the proposed algorithms. Results show that the heuristics perform better for test problems of larger size and the genetic algorithms perform better for smaller size problems.
Persistent Identifierhttp://hdl.handle.net/10722/158834
References
References in Scopus

 

DC FieldValueLanguage
dc.contributor.authorLu, Hen_US
dc.contributor.authorHuang, GQen_US
dc.contributor.authorDai, Qen_US
dc.date.accessioned2012-08-08T09:03:32Z-
dc.date.available2012-08-08T09:03:32Z-
dc.date.issued2010en_US
dc.identifier.citation40Th International Conference On Computers And Industrial Engineering: Soft Computing Techniques For Advanced Manufacturing And Service Systems, Cie40 2010, 2010en_US
dc.identifier.urihttp://hdl.handle.net/10722/158834-
dc.description.abstractAssembly jobs can be seen as a more generalized version of traditional jobs. A traditional job refers to one with only sequential operations while an assembly job refers to one with additional assembly operations and complex product structures. This research proposes and compares genetic algorithms and heuristics for scheduling assembly jobs. The objective is to minimize the makespan (maximum completion time) of a given set of assembly jobs. Experiments have been conducted to compare the performance of the proposed algorithms. Results show that the heuristics perform better for test problems of larger size and the genetic algorithms perform better for smaller size problems.en_US
dc.languageengen_US
dc.relation.ispartof40th International Conference on Computers and Industrial Engineering: Soft Computing Techniques for Advanced Manufacturing and Service Systems, CIE40 2010en_US
dc.subjectAssembly Job Shopen_US
dc.subjectBackward Schedulingen_US
dc.subjectForward Schedulingen_US
dc.subjectGenetic Algorithmen_US
dc.subjectHeuristicsen_US
dc.titleHeuristics and genetic algorithms for minimizing makespan of assembly jobsen_US
dc.typeConference_Paperen_US
dc.identifier.emailHuang, GQ:gqhuang@hkucc.hku.hken_US
dc.identifier.authorityHuang, GQ=rp00118en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1109/ICCIE.2010.5668255en_US
dc.identifier.scopuseid_2-s2.0-78651436755en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-78651436755&selection=ref&src=s&origin=recordpageen_US
dc.identifier.scopusauthoridLu, H=35146299500en_US
dc.identifier.scopusauthoridHuang, GQ=7403425048en_US
dc.identifier.scopusauthoridDai, Q=7202735140en_US

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