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Generalized data model for real-world capacitated lot-sizing problems with linked lot sizes and backorders

This data article establishes the first data model for the Multi-Level Capacitated Lot-Sizing Problem with Linked Lot Sizes and Backorders (MLCLSP-L-B) for tablets manufacturing processes. The dataset consists out of nine tables and collects all required meta-information for capacitated lot-sizing p...

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Detalles Bibliográficos
Autores principales: Simonis, Michael, Nickel, Stefan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10405180/
https://www.ncbi.nlm.nih.gov/pubmed/37554992
http://dx.doi.org/10.1016/j.dib.2023.109440
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author Simonis, Michael
Nickel, Stefan
author_facet Simonis, Michael
Nickel, Stefan
author_sort Simonis, Michael
collection PubMed
description This data article establishes the first data model for the Multi-Level Capacitated Lot-Sizing Problem with Linked Lot Sizes and Backorders (MLCLSP-L-B) for tablets manufacturing processes. The dataset consists out of nine tables and collects all required meta-information for capacitated lot-sizing problems with linked lot sizes and backorders. Furthermore, it is compatible to store information for single- and multi-level lot-sizing problem instance information. An exact field description and field type is provided for each table. Anonymized real-world data represents four single-level packaging and five multi-level tablets manufacturing processes that are shared with lot-sizing research community by the standardized data template.
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spelling pubmed-104051802023-08-08 Generalized data model for real-world capacitated lot-sizing problems with linked lot sizes and backorders Simonis, Michael Nickel, Stefan Data Brief Data Article This data article establishes the first data model for the Multi-Level Capacitated Lot-Sizing Problem with Linked Lot Sizes and Backorders (MLCLSP-L-B) for tablets manufacturing processes. The dataset consists out of nine tables and collects all required meta-information for capacitated lot-sizing problems with linked lot sizes and backorders. Furthermore, it is compatible to store information for single- and multi-level lot-sizing problem instance information. An exact field description and field type is provided for each table. Anonymized real-world data represents four single-level packaging and five multi-level tablets manufacturing processes that are shared with lot-sizing research community by the standardized data template. Elsevier 2023-07-22 /pmc/articles/PMC10405180/ /pubmed/37554992 http://dx.doi.org/10.1016/j.dib.2023.109440 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Data Article
Simonis, Michael
Nickel, Stefan
Generalized data model for real-world capacitated lot-sizing problems with linked lot sizes and backorders
title Generalized data model for real-world capacitated lot-sizing problems with linked lot sizes and backorders
title_full Generalized data model for real-world capacitated lot-sizing problems with linked lot sizes and backorders
title_fullStr Generalized data model for real-world capacitated lot-sizing problems with linked lot sizes and backorders
title_full_unstemmed Generalized data model for real-world capacitated lot-sizing problems with linked lot sizes and backorders
title_short Generalized data model for real-world capacitated lot-sizing problems with linked lot sizes and backorders
title_sort generalized data model for real-world capacitated lot-sizing problems with linked lot sizes and backorders
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10405180/
https://www.ncbi.nlm.nih.gov/pubmed/37554992
http://dx.doi.org/10.1016/j.dib.2023.109440
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