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dc.contributor.authorKuo-Ching, Ying
dc.contributor.authorFabio, Fruggiero
dc.contributor.authorPourhejazy, Pourya
dc.contributor.authorBo-Yun, Lee
dc.date.accessioned2022-03-24T08:29:52Z
dc.date.available2022-03-24T08:29:52Z
dc.date.issued2022-03-19
dc.description.abstractAs a disruptive technology, additive manufacturing (AM) is revolutionizing manufacturing supply chains. AM consists of producing 3-dimensional objects through layer-by-layer addition of compound material based on digital models. The scheduling of additive manufacturing operations differs from traditional (i.e., subtractive and injection molding) manufacturing with a single production run involving several parts/geometries;::; this makes the jobs heterogeneous. Limited studies have investigated the Additive Manufacturing Scheduling Problems (AMSP). This study extends the Iterated Greedy algorithm to solve the AMSPs considering a single-machine production setting. For this purpose, several computational mechanisms are customized to account for AMspecific characteristics of production scheduling. Numerical analysis shows that the vast majority of the bestfound solutions are yielded by the Adjusted Iterated Greedy (AIG) algorithm considering both solution quality and stability; the outperformance becomes more significant with an increase in problem size. Statistical analysis confirms that AIG’s performance is notably better than that of the existing solution algorithm in terms of solution quality and stability. This study is concluded by providing directions for future development of AM and AMSPs to extend the industrial reach of 3D printing technology.en_US
dc.identifier.citationKuo-Ching, Fabio, Pourhejazy P, Bo-Yun. Adjusted Iterated Greedy for the optimization of additive manufacturing scheduling problems. Expert Systems With Applications. 2022;198en_US
dc.identifier.cristinIDFRIDAID 2011849
dc.identifier.doihttps://doi.org/10.1016/j.eswa.2022.116908
dc.identifier.issn0957-4174
dc.identifier.issn1873-6793
dc.identifier.urihttps://hdl.handle.net/10037/24523
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.relation.journalExpert Systems With Applications
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2022 The Author(s)en_US
dc.titleAdjusted Iterated Greedy for the optimization of additive manufacturing scheduling problemsen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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