Optimization Model and Strategy for Dynamic Material Distribution Scheduling Based on Digital Twin Article Swipe
Zhongfei Zhang
,
Ting Qu
,
Kuo Zhao
,
Kai Zhang
,
Yongheng Zhang
,
Lei Liu
,
Jun Wang
,
George Q. Huang
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.20944/preprints202311.0071.v1
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.20944/preprints202311.0071.v1
. Manufacturers are increasingly adopting mixed-flow manufacturing models to meet the growing customized, diverse, and dynamic customer demand. In such an environment, material distribution scheduling optimization is vital for smooth operations and is integral to production management. However, manufacturers frequently encounter problems like disordered and delayed material distribution. Traditional scheduling methods suffer from problems like inadequate transparency, delayed decision directives, and suboptimal results, impacting performance. To this end, this study proposes a dynamic material distribution scheduling optimization model and strategy based on digital twin (DT) to address these problems. Firstly, we introduce workstation satisfaction and establish a material distribution path optimization model minimizing total distribution cost while maximizing workstation satisfaction. Subsequently, we present a cloud-edge computing-based decision framework and explain the DT-based material distribution system's components and operation. Furthermore, a dynamic material distribution scheduling optimization mechanism based on DT is designed. By incorporating a savings method and incentive, penalty strategies, improvements are made to the path node selection probabilities and the information pheromone update rules of the traditional ant colony optimization (ACO) algorithm. Finally, a numerical case study, using real data from collaborating enterprises, validates the proposed algorithm and strategy. This research offers valuable insights into logistics management and algorithm design in smart manufacturing environments.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.20944/preprints202311.0071.v1
- https://www.preprints.org/manuscript/202311.0071/v1/download
- OA Status
- green
- Cited By
- 1
- References
- 27
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4388226504
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- OpenAlex ID
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https://openalex.org/W4388226504Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.20944/preprints202311.0071.v1Digital Object Identifier
- Title
-
Optimization Model and Strategy for Dynamic Material Distribution Scheduling Based on Digital TwinWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-11-02Full publication date if available
- Authors
-
Zhongfei Zhang, Ting Qu, Kuo Zhao, Kai Zhang, Yongheng Zhang, Lei Liu, Jun Wang, George Q. HuangList of authors in order
- Landing page
-
https://doi.org/10.20944/preprints202311.0071.v1Publisher landing page
- PDF URL
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https://www.preprints.org/manuscript/202311.0071/v1/downloadDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://www.preprints.org/manuscript/202311.0071/v1/downloadDirect OA link when available
- Concepts
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Ant colony optimization algorithms, Computer science, Scheduling (production processes), Mathematical optimization, Workstation, Dynamic priority scheduling, Material flow, Distributed computing, Industrial engineering, Engineering, Schedule, Algorithm, Mathematics, Ecology, Operating system, BiologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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27Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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