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Instance dataset for resource-constrained project scheduling with diverging material flows
This data article describes an instance dataset motivated by the problem of scheduling a project with diverging material flows. Such material flows are released during the execution of the project and are subject to limited processing and storage capacities. Typical examples are nuclear dismantling...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10294052/ https://www.ncbi.nlm.nih.gov/pubmed/37383755 http://dx.doi.org/10.1016/j.dib.2023.109279 |
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author | Gehring, Marco Volk, Rebekka Schultmann, Frank |
author_facet | Gehring, Marco Volk, Rebekka Schultmann, Frank |
author_sort | Gehring, Marco |
collection | PubMed |
description | This data article describes an instance dataset motivated by the problem of scheduling a project with diverging material flows. Such material flows are released during the execution of the project and are subject to limited processing and storage capacities. Typical examples are nuclear dismantling or other deconstruction/demolition projects, where large amounts of material must be classified, scanned for hazardousness, and processed accordingly. The problem setting is mathematically described as a resource-constrained project scheduling problem with cumulative resources (RCPSP/c). The RCPSP/c deals with finding a project schedule with minimal makespan that satisfies temporal, renewable resource, and cumulative resource constraints. In total, the dataset comprises 192 artificially generated instances that are suitable for testing models and solution methods. In addition, we provide our best found solution for each instance and different modeling variants (e.g., for two types of objective functions). These solutions were computed by heuristic solution methods. The dataset serves as a benchmark for researchers evaluating the performance of solution methods for the RCPSP/c or the more general problem class with resources that can be produced and consumed. |
format | Online Article Text |
id | pubmed-10294052 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-102940522023-06-28 Instance dataset for resource-constrained project scheduling with diverging material flows Gehring, Marco Volk, Rebekka Schultmann, Frank Data Brief Data Article This data article describes an instance dataset motivated by the problem of scheduling a project with diverging material flows. Such material flows are released during the execution of the project and are subject to limited processing and storage capacities. Typical examples are nuclear dismantling or other deconstruction/demolition projects, where large amounts of material must be classified, scanned for hazardousness, and processed accordingly. The problem setting is mathematically described as a resource-constrained project scheduling problem with cumulative resources (RCPSP/c). The RCPSP/c deals with finding a project schedule with minimal makespan that satisfies temporal, renewable resource, and cumulative resource constraints. In total, the dataset comprises 192 artificially generated instances that are suitable for testing models and solution methods. In addition, we provide our best found solution for each instance and different modeling variants (e.g., for two types of objective functions). These solutions were computed by heuristic solution methods. The dataset serves as a benchmark for researchers evaluating the performance of solution methods for the RCPSP/c or the more general problem class with resources that can be produced and consumed. Elsevier 2023-05-29 /pmc/articles/PMC10294052/ /pubmed/37383755 http://dx.doi.org/10.1016/j.dib.2023.109279 Text en © 2023 The Authors. Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Gehring, Marco Volk, Rebekka Schultmann, Frank Instance dataset for resource-constrained project scheduling with diverging material flows |
title | Instance dataset for resource-constrained project scheduling with diverging material flows |
title_full | Instance dataset for resource-constrained project scheduling with diverging material flows |
title_fullStr | Instance dataset for resource-constrained project scheduling with diverging material flows |
title_full_unstemmed | Instance dataset for resource-constrained project scheduling with diverging material flows |
title_short | Instance dataset for resource-constrained project scheduling with diverging material flows |
title_sort | instance dataset for resource-constrained project scheduling with diverging material flows |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10294052/ https://www.ncbi.nlm.nih.gov/pubmed/37383755 http://dx.doi.org/10.1016/j.dib.2023.109279 |
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