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dc.contributor.authorLinet, Özdamar
dc.date.accessioned2014-11-05T11:42:13Z
dc.date.available2014-11-05T11:42:13Z
dc.date.issued1999-08
dc.identifier.issn0160-5682
dc.identifier.urihttp://hdl.handle.net/11413/809
dc.description.abstractThe multi-stage capacitated lot sizing and loading problem (MCLSLP) deals with the issue of determining the lot sizes of product items in serially-arranged manufacturing stages and loading them on parallel facilities in each stage to satisfy dynamic demand over a given planning horizon. It is assumed that regular time capacity decisions have already been made in the tactical level and allocated to the stages, but it is still an important decision problem whether to augment regular time capacity by overtime capacity. Each item may be processed on a technologically feasible subset of existing facilities with different process and setup times on each facility. Since the solution of the MCLSLP requires the design of a powerful algorithm, simulated annealing (SA) and genetic algorithms (GA) are integrated to enhance their individual performances. Furthermore, these global optimisation methods are incorporated into a Lagrangean relaxation scheme, hence creating a hybrid solution methodology. Numerical results obtained using these methods confirm the mutual benefits of integrating different solution techniques.tr_TR
dc.language.isoen_UStr_TR
dc.publisherSTOCKTON PRESS, HOUNDMILLS, BASINGSTOKE RG21 6XS, HAMPSHIRE, ENGLANDtr_TR
dc.relationJOURNAL OF THE OPERATIONAL RESEARCH SOCIETYtr_TR
dc.subjectHeuristicstr_TR
dc.subjectSimulated Annealingtr_TR
dc.subjectGenetic Algorithmstr_TR
dc.subjectLagrangean Relaxationtr_TR
dc.subjectMulti-stage Lot Sizingtr_TR
dc.subjectSezgisellertr_TR
dc.subjectIsıl İşlemtr_TR
dc.subjectGenetik Algoritmalartr_TR
dc.subjectLagrange Rahatlamatr_TR
dc.subjectÇok Aşamalı Parti Büyüklüğütr_TR
dc.titleHybrid Heuristics for the Multi-stage Capacitated Lot Sizing and Loading Problemtr_TR
dc.typeArticletr_TR


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