Abstract
Digital twin is considered an alternative for optimizing real-world performance within virtual context, which also applies to the optimization of Supply Chain Management (SCM). Blockchain, which facilitates data secure storage and trusted tracking, is deemed to be a proper assistant technology for achieving digital twin implementation. In this work, we propose a blockchain-based digital twin solution to reengineer SCM system, which promotes the digitization and intelligence of SCM to fit in massive service volumes in complex-intercrossed industry system. A strong-weak consensus mode is developed to achieve energy and time savings. We also design intelligent switch-based algorithms to generate time-saving consensus plans under energy constraints. Finally, we set up multiple experiments to compare our algorithm with three baseline algorithms, including Effective Iterative Greedy (EIG), Two Dimensional Genetic (TDG), and High-level Task Scheduling Dynamic Programming (HTSDP). Findings from evaluation demonstrate the potential of our proposed model. Specifically, our algorithm reduces time and energy consumption of EIG algorithm in consensus by 46.84% and 16.25%, respectively. Compared with TDG algorithm, consensus time and energy consumption of our algorithm are reduced by 50.05% and 48.46%. Our algorithm cuts down time spent of HTSDP algorithm in generating consensus plan by a factor of 9.88.
| Original language | English |
|---|---|
| Pages (from-to) | 1673-1685 |
| Number of pages | 13 |
| Journal | IEEE Transactions on Services Computing |
| Volume | 16 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 1 May 2023 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 7 Affordable and Clean Energy
Keywords
- Digital twin
- blockchain
- consensus
- optimization
- supply chain management
Fingerprint
Dive into the research topics of 'Blockchain-Enabled Service Optimizations in Supply Chain Digital Twin'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver