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Determination of due dates in job shop scheduling by simulated annealing

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dc.contributor.author Mamalis, AG en
dc.contributor.author Malagardis, I en
dc.date.accessioned 2014-03-01T01:11:52Z
dc.date.available 2014-03-01T01:11:52Z
dc.date.issued 1996 en
dc.identifier.issn 0951-5240 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/11839
dc.subject simulation en
dc.subject simulated annealing en
dc.subject manufacturing systems en
dc.subject production planning en
dc.subject group technology en
dc.subject.classification Computer Science, Interdisciplinary Applications en
dc.subject.classification Engineering, Manufacturing en
dc.subject.classification Operations Research & Management Science en
dc.title Determination of due dates in job shop scheduling by simulated annealing en
heal.type journalArticle en
heal.identifier.primary 10.1016/0951-5240(95)00039-9 en
heal.identifier.secondary http://dx.doi.org/10.1016/0951-5240(95)00039-9 en
heal.language English en
heal.publicationDate 1996 en
heal.abstract The scheduling of n jobs to m machines in a job shop is considered. A predefined due date, a release time and the minimization of the maximal job's lateness is the objective assigned to each job. A search space consisting of triads (job, operation, machine) is formulated, and an iterrative improvement approach, the simulated annealing method, is then used to obtain feasible and global optimal solution. The simulated annealing method is applied to two alternative energy functions to model the maximum lateness. For calculation of the first energy function at each step, complete schedules are created and the lateness of each job is derived by abstracting the job's completion time from the corresponding due date. The second energy function is calculated on the basis of partial estimates often used by pairwise interchange techniques. The convergence of the algorithm in relation to the initial temperature, temperature iterrations and temperature cycles has been verified in various case studies. Specific characteristics of the scheduling, such as its dimensionality and the deviation of the total processing time from the due dates, were considered. Common characteristics derived were subsequently used for the definition of an efficient annealing schedule. Copyright (C) 1996 Published by Elsevier Science Ltd en
heal.publisher BUTTERWORTH-HEINEMANN LTD en
heal.journalName COMPUTER INTEGRATED MANUFACTURING SYSTEMS en
dc.identifier.doi 10.1016/0951-5240(95)00039-9 en
dc.identifier.isi ISI:A1996UV03100001 en
dc.identifier.volume 9 en
dc.identifier.issue 2 en
dc.identifier.spage 65 en
dc.identifier.epage 72 en


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