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dc.contributor.authorKirchhof, Michael-
dc.contributor.authorMeyer, Oliver-
dc.contributor.authorWeihs, Claus-
dc.date.accessioned2019-03-22T08:14:57Z-
dc.date.available2019-03-22T08:14:57Z-
dc.date.issued2019-03-08-
dc.identifier.urihttp://hdl.handle.net/2003/37950-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-19935-
dc.description.abstractIn the process of manufacturing various products, a larger production item is first produced and subsequently smaller parts are cut out of it. In this report we present three algorithms that find optimal positions of production pieces to be cut out of a larger production item. The algorithms are able to consider multiple quality parameters and optimize them in a given priority order. They guarantee different levels of optimality and therefore differ in their required computing time and memory usage. We assemble these algorithms with respect to each’s specific benefits and drawbacks and in adaption to the given computational resources. If possible, the process is sped up by splitting the search for pieces on the whole production item into several local searches. Lastly, the approach is embedded into an application with a graphical user interface to enable its use in the industry.en
dc.language.isoende
dc.relation.ispartofseriesTechnical Report;1/2019-
dc.subjectbattery productionen
dc.subjectknapsack algorithmen
dc.subjectoptimizationen
dc.subjectsoftware developmenten
dc.subject.ddc310-
dc.titleCutting Optimal Pieces from Production Itemsen
dc.typeTextde
dc.type.publicationtypereportde
dc.subject.rswkRucksackproblemde
dc.subject.rswkOptimierungde
dc.subject.rswkSoftwareentwicklungde
dc.subject.rswkBatteriede
dcterms.accessRightsopen access-
eldorado.secondarypublicationfalsede
Appears in Collections:Lehrstuhl Computergestützte Statistik

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