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Three genetic algorithm approaches to parallel machine scheduling and comparison with a heuristic

dc.contributor.authorsSamur S., Bulkan S.
dc.date.accessioned2022-03-15T01:57:48Z
dc.date.accessioned2026-01-11T05:58:01Z
dc.date.available2022-03-15T01:57:48Z
dc.date.issued2010
dc.description.abstractIn this research, we aim to assign jobs, having different processing and release times, to identical parallel machines in the most effective way. To do so; firstly we made a literature review to see what other researchers have done in this area. Secondly, we proposed three genetic algorithms each having different crossover methods. And at the end; we examined those three algorithms and also a heuristic which we already proposed and tested before. Based on the job size and machine size, some algorithms performed better results than others. © 2010 IEEE.
dc.identifier.doi10.1109/ITNG.2010.184
dc.identifier.isbn9780769539843
dc.identifier.urihttps://hdl.handle.net/11424/247005
dc.language.isoeng
dc.relation.ispartofITNG2010 - 7th International Conference on Information Technology: New Generations
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectGenetic algorithm
dc.subjectHeuristic
dc.subjectMakespan
dc.subjectParallel machine scheduling
dc.subjectRelease time
dc.titleThree genetic algorithm approaches to parallel machine scheduling and comparison with a heuristic
dc.typeconferenceObject
dspace.entity.typePublication
oaire.citation.endPage274
oaire.citation.startPage270
oaire.citation.titleITNG2010 - 7th International Conference on Information Technology: New Generations

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