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Control of manufacturing networks which contain a batch processing machine

dc.contributor.authorNeale, John J.en_US
dc.contributor.authorDuenyas, Izaken_US
dc.date.accessioned2006-09-11T17:10:02Z
dc.date.available2006-09-11T17:10:02Z
dc.date.issued2000-11en_US
dc.identifier.citationNeale, John J.; Duenyas, Izak; (2000). "Control of manufacturing networks which contain a batch processing machine." IIE Transactions 32(11): 1027-1041. <http://hdl.handle.net/2027.42/45931>en_US
dc.identifier.issn0740-817Xen_US
dc.identifier.issn1573-9724en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/45931
dc.description.abstractWe consider the control of a batch processing machine which is part of a larger manufacturing network of machines. Systems consisting of a batch processing machine and one or more unit-capacity machines in tandem are considered. The objective is to minimize the average time that jobs spend in the entire system. We present algorithms to determine the optimal policies for certain finite horizon, deterministic problems. We then discuss the structure of the optimal policies for infinite horizon, stochastic problems, and investigate the benefit of utilizing information about upstream and downstream unit-capacity machines in the control of the batch machine. We develop a simple heuristic scheduling policy to control the batch machine which takes into account the state of other machines in the network. Computational results demonstrate the effectiveness of our heuristic over a wide range of problem instances.en_US
dc.format.extent175958 bytes
dc.format.extent3115 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherKluwer Academic Publishers; Springer Science+Business Mediaen_US
dc.subject.otherEngineeringen_US
dc.subject.otherMechanical Engineeringen_US
dc.titleControl of manufacturing networks which contain a batch processing machineen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelIndustrial and Operations Engineeringen_US
dc.subject.hlbsecondlevelMathematicsen_US
dc.subject.hlbsecondlevelManagementen_US
dc.subject.hlbsecondlevelEconomicsen_US
dc.subject.hlbtoplevelBusinessen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI, 48109, USAen_US
dc.contributor.affiliationumThe Business School, University of Michigan, Ann Arbor, MI, 48109, USAen_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/45931/1/10756_2004_Article_274353.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1023/A:1013780307222en_US
dc.identifier.sourceIIE Transactionsen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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