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Optimization Based Job Shop Scheduling

dc.contributor.authorMusser, K.L.en_US
dc.contributor.authorDhingra, Jastej S.en_US
dc.contributor.authorBlankenehip, Gilmer L.en_US
dc.description.abstractA generalized job shop scheduling problem is defined in detail. The proposed factory description is sufficiently realistic to model the routing and sequencing decisions made in a real manufacturing plant. An optimization problem is posed, permitting the use of very general cost functions. A variation of the method of simulated annealing is proposed as a tool for the solution of the optimization problem. A novel technique for embedding the space of feasible schedules into a permutation group is used to define a neighborhood structure for the simulated annealing process. This technique has algorithmic advantages over working directly in the space of schedules. These ideas were used to construct a scheduling software system which is in use at a Texas Instruments Custom Manufacturing Unit. We give a brief description of the software system, called ABES for Annealing Based Experiment in Scheduling, and comment on its effectiveness.en_US
dc.format.extent985007 bytes
dc.relation.ispartofseriesISR; TR 1991-9en_US
dc.subjectdiscrete event dynamical systems en_US
dc.subjectflexible manufacturingen_US
dc.subjectManufacturing Systemsen_US
dc.titleOptimization Based Job Shop Schedulingen_US
dc.typeTechnical Reporten_US

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