Compound Matrix-Based Project Database (CMPD)

The impact of projects is vital, from business operations to research to the national economy. Therefore, management science and operation research have extensively studied project scheduling and resource allocation for over six decades. Project databases were proposed to test algorithms, including...

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Veröffentlicht in:Scientific data Jg. 11; H. 1; S. 319 - 10
Hauptverfasser: Kosztyán, Zsolt T., Novák, Gergely L.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London Nature Publishing Group UK 27.03.2024
Nature Publishing Group
Nature Portfolio
Schlagworte:
706/703/559
706/703/66
Algorithms
Data Descriptor
Humanities and Social Sciences
multidisciplinary
Project management
Resource allocation
Science
Science (multidisciplinary)
ISSN:2052-4463, 2052-4463
Online-Zugang:Volltext
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Zusammenfassung:The impact of projects is vital, from business operations to research to the national economy. Therefore, management science and operation research have extensively studied project scheduling and resource allocation for over six decades. Project databases were proposed to test algorithms, including simulated or real, single or multiprojects, and single-mode or multi-mode projects. However, the dozens of project databases are extremely heterogeneous regarding the file structure and the features of the modeled projects. Furthermore, the efficiency and performance of project scheduling and resource allocation algorithms are susceptible to the characteristics of projects. Therefore, the proposed Compound Matrix-Based Project Database (CMPD) collects and consolidates the most frequently used project databases. The proposed Unified Matrix-Based Project-Planning Model (UMP) sparse matrix-based model enables the addition of new features to existing project structures, such as completion priorities, structural flexibility, and quality parameters, to broaden the scope of considered projects and to take account of flexible approaches, such as agile, extreme, and hybrid projects.
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ISSN:2052-4463
2052-4463
DOI:10.1038/s41597-024-03154-x