Multi-skill resource-constrained multi-modal project scheduling problem based on hybrid quantum algorithm
Abstract Numerous studies on project scheduling only consider a single factor, which fails to reflect the actual environment of project operations. In light of this issue, the article synthesizes multiple perspectives and proposes a multi-skill resource-based multi-modal project scheduling problem (...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-10-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-45970-y |
| _version_ | 1797647260737077248 |
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| author | Jun Long Peng Xiao Liu Chao Peng Yu Shao |
| author_facet | Jun Long Peng Xiao Liu Chao Peng Yu Shao |
| author_sort | Jun Long Peng |
| collection | DOAJ |
| description | Abstract Numerous studies on project scheduling only consider a single factor, which fails to reflect the actual environment of project operations. In light of this issue, the article synthesizes multiple perspectives and proposes a multi-skill resource-based multi-modal project scheduling problem (MRCMPSP). This problem is described, modeled, and solved using the resource capability matrix and other constraints to minimize the project duration. To effectively solve MRCMPSP and enrich scheduling algorithms, the paper selects the hybrid quantum algorithm (HQPSO) based on the quantum particle swarm algorithm (QPSO). The HQPSO introduces various improvements such as the JAYA optimization search to improve the algorithm's performance. In order to verify the generality, superiority, and effectiveness of the algorithm, independent operation comparison experiments and practical application experiments of the algorithm are designed based on different case sizes and resource quantities. The experimental results demonstrate that the proposed algorithm has superior convergence performance and solution accuracy and can provide an effective scheduling solution for real cases. Additionally, the article provides targeted management suggestions based on the research findings. Overall, this study contributes a novel mathematical model, solution algorithm, optimization strategies, and managerial insights, advancing the field of project management research. |
| first_indexed | 2024-03-11T15:14:44Z |
| format | Article |
| id | doaj.art-606dba2f03d740669a147401cbf090f7 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-11T15:14:44Z |
| publishDate | 2023-10-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-606dba2f03d740669a147401cbf090f72023-10-29T12:24:54ZengNature PortfolioScientific Reports2045-23222023-10-0113111710.1038/s41598-023-45970-yMulti-skill resource-constrained multi-modal project scheduling problem based on hybrid quantum algorithmJun Long Peng0Xiao Liu1Chao Peng2Yu Shao3Changsha University of Science & TechnologyChangsha University of Science & TechnologyChina State Construction Hailong TechnologyChangsha University of Science & TechnologyAbstract Numerous studies on project scheduling only consider a single factor, which fails to reflect the actual environment of project operations. In light of this issue, the article synthesizes multiple perspectives and proposes a multi-skill resource-based multi-modal project scheduling problem (MRCMPSP). This problem is described, modeled, and solved using the resource capability matrix and other constraints to minimize the project duration. To effectively solve MRCMPSP and enrich scheduling algorithms, the paper selects the hybrid quantum algorithm (HQPSO) based on the quantum particle swarm algorithm (QPSO). The HQPSO introduces various improvements such as the JAYA optimization search to improve the algorithm's performance. In order to verify the generality, superiority, and effectiveness of the algorithm, independent operation comparison experiments and practical application experiments of the algorithm are designed based on different case sizes and resource quantities. The experimental results demonstrate that the proposed algorithm has superior convergence performance and solution accuracy and can provide an effective scheduling solution for real cases. Additionally, the article provides targeted management suggestions based on the research findings. Overall, this study contributes a novel mathematical model, solution algorithm, optimization strategies, and managerial insights, advancing the field of project management research.https://doi.org/10.1038/s41598-023-45970-y |
| spellingShingle | Jun Long Peng Xiao Liu Chao Peng Yu Shao Multi-skill resource-constrained multi-modal project scheduling problem based on hybrid quantum algorithm Scientific Reports |
| title | Multi-skill resource-constrained multi-modal project scheduling problem based on hybrid quantum algorithm |
| title_full | Multi-skill resource-constrained multi-modal project scheduling problem based on hybrid quantum algorithm |
| title_fullStr | Multi-skill resource-constrained multi-modal project scheduling problem based on hybrid quantum algorithm |
| title_full_unstemmed | Multi-skill resource-constrained multi-modal project scheduling problem based on hybrid quantum algorithm |
| title_short | Multi-skill resource-constrained multi-modal project scheduling problem based on hybrid quantum algorithm |
| title_sort | multi skill resource constrained multi modal project scheduling problem based on hybrid quantum algorithm |
| url | https://doi.org/10.1038/s41598-023-45970-y |
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