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Scheduling with Sequencing Flexibility *

dc.contributor.authorRachamadugu, Ram V.en_US
dc.contributor.authorNandkeolyar, Udayanen_US
dc.contributor.authorSchriber, Tomen_US
dc.date.accessioned2010-06-01T20:47:37Z
dc.date.available2010-06-01T20:47:37Z
dc.date.issued1993-03en_US
dc.identifier.citationRachamadugu, Ram; Nandkeolyar, Udayan; Schriber, Tom (1993). "Scheduling with Sequencing Flexibility * ." Decision Sciences 24(2): 315-342. <http://hdl.handle.net/2027.42/73893>en_US
dc.identifier.issn0011-7315en_US
dc.identifier.issn1540-5915en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/73893
dc.description.abstractThis study examines the effects of sequencing flexibility on the performance of rules used to schedule operations in manufacturing systems. The findings show that taking advantage of even low levels of sequencing flexibility in the set of operations required to do a job results in substantial improvement in the performance of scheduling rules with respect to mean flowtime. Differences in the mean flowtime measure for various rules also diminish significantly with increasing sequencing flexibility. Performance improvements additionally result for such due-date related performance measures as mean tardiness and the proportion of jobs tardy. At high levels of sequencing flexibility, some nonparametric scheduling rules outperform the shortest processing time rule in terms of the mean flowtime criterion. Rules based on job due dates also outperform rules based on operation milestones in terms of tardiness related criteria at high levels of sequencing flexibility. The implications of these findings for the design of manufacturing systems and product design are noted.en_US
dc.format.extent1535925 bytes
dc.format.extent3109 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.publisherBlackwell Publishing Ltden_US
dc.rights1993 by the American Institute for Decision Sciencesen_US
dc.subject.otherProduction/Operations Management and Schedulingen_US
dc.titleScheduling with Sequencing Flexibility *en_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelComputer Scienceen_US
dc.subject.hlbsecondlevelMathematicsen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumCIS Department, Graduate School of Business, The University of Michigan, Ann Arbor, MI 48109en_US
dc.contributor.affiliationotherISOM Department, College of Business Administration, The University of Toledo, Toledo, OH 43606en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/73893/1/j.1540-5915.1993.tb00477.x.pdf
dc.identifier.doi10.1111/j.1540-5915.1993.tb00477.xen_US
dc.identifier.sourceDecision Sciencesen_US
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dc.owningcollnameInterdisciplinary and Peer-Reviewed


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