Collaborative Business Modeling and Parallel Optimization Algorithm for Blockchain

SHANGGUAN Zizhuo; LI Donghe; YANG Qingyu

doi:10.7652/xjtuxb202412013

您当前的位置：

首页 >

文章列表页 >

Collaborative Business Modeling and Parallel Optimization Algorithm for Blockchain

更新时间：2025-07-28

- Collaborative Business Modeling and Parallel Optimization Algorithm for Blockchain
- Vol. 58, Issue 12, Pages: 131-140(2024)
- 作者机构：
  
  1. 西安交通大学自动化科学与工程学院,西安,710049
  2. 西安交通大学精密微纳制造技术全国重点实验室,西安,710049
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb202412013
  CLC： TP3
- Online First：10 December 2024，
  
  Published：2024
- 稿件说明：
移动端阅览
SHANGGUAN Zizhuo, LI Donghe, YANG Qingyu. Collaborative Business Modeling and Parallel Optimization Algorithm for Blockchain[J]. 2024, 58(12): 131-140.
DOI：

SHANGGUAN Zizhuo, LI Donghe, YANG Qingyu. Collaborative Business Modeling and Parallel Optimization Algorithm for Blockchain[J]. 2024, 58(12): 131-140. DOI： 10.7652/xjtuxb202412013.

摘要

针对供应链管理面临的协同高效性、信息可追溯性和信任危机等问题

提出了一个解决区块链多要素矛盾问题的并行计算模型PNSGA-Ⅲ。首先

深入挖掘区块链、链主企业和链上企业的制约关系

将链主企业成本、服务积分

链上企业参与数量以及区块链稳定性等参数具象为多级多业务协同模型; 其次

从提高遗传算法产生子代缓存区的效率角度出发

将交叉变异部分并行化处理

极大缩短模型求解时间; 此外

为了解决帕累托解不能相互支配的问题

采用TOPSIS计算欧氏距离并决策理想解; 最后

通过10组仿真实验验证了所提模型的有效性。结果表明:PNSGA-Ⅲ的计算时间比非并行算法节约了16.37%; 区块链的矛盾制约机制提供了更广泛的选择范围

增强了其适应复杂需求的能力; 在动态任务流程下

经过优化的S8场景的服务积分比未优化的场景高出45%。研究为供应链管理提供了新的视角和工具。

Abstract

In response to challenges encountered in supply chain management such as collaborative efficiency

information traceability

and trust crises

a parallel computing model

PNSGA-Ⅲ

is introduced to tackle the multifaceted issues in blockchain. Initially

by exploring the interactions among blockchain

the blockchain lead enterprises(BLEs)

and blockchain on-chain enterprises(BOEs)

parameters such as costs for BLEs

service points

the number of participating BOEs

and blockchain stability are transformed into a multi-level multi-business collaborative model. Subsequently

to enhance the efficiency of the genetic algorithm in generating offspring cache areas

the crossover and mutation components are processed in parallel

leading to a substantial reduction in the model's solution time. Furthermore

to handle the challenge of non-mutually dominant Pareto solutions

TOPSIS is employed to calculate the Euclidean distance and determine the optimal solutions. Finally

the effectiveness of the proposed model is verified through 10 sets of simulation experiments. The results indicate that the computation time of PNSGA-Ⅲ is 16.37% shorter than that of non-parallel algorithms. The conflicting constraint mechanism of blockchain provides a wider range of options

enhancing its adaptability to complex requirements. Under dynamic task flows

the service points of the optimized S8 solution are 45% higher than those of the unoptimized solution. This research provides fresh insights and tools for advancing supply chain management practices.

关键词

Keywords

references

刘路, 李文欣, 宋晓, 等. 基于模糊群决策的绿色供应商选择和订单分配方法 [J]. 系统仿真学报, 2023, 35(10): 2133-2149.

LIU Lu, LI Wenxin, SONG Xiao, et al. A fuzzy group decision-making-based method for green supplier selection and order allocation [J]. Journal of System Simulation, 2023, 35(10): 2133-2149.

张梦钗. 考虑云制造订单协同分配与动态接受的生产调度研究 [D]. 杭州: 杭州电子科技大学, 2022.

孙德琳. 供应不确定环境下J企业采购订单分配研究 [D]. 北京: 北京交通大学, 2022.

XU Mengtian, FENG Guorui, REN Yanli, et al. On cloud storage optimization of blockchain with a clustering-based genetic algorithm [J]. IEEE Internet of Things Journal, 2020, 7(9): 8547-8558.

TAPSCOTT D A. Blockchain revolution: how the technology behind bitcoin is changing money, business, and the world [M]. New York, USA: Portfolio, 2016.

张乐君, 刘智栋, 谢国, 等. 基于集成信用度评估智能合约的安全数据共享模型 [J]. 自动化学报, 2021, 47(3): 594-608.

ZHANG Lejun, LIU Zhidong, XIE Guo, et al. Secure data sharing model based on smart contract with integrated credit evaluation [J]. Acta Automatica Sinica, 2021, 47(3): 594-608.

LI Yilin, LI Donghe, YANG Qingyu. A blockchain-based semi-centralized business system for multi-enterprise [C]//The 42nd Chinese Control Conference. Piscataway, NJ, USA: IEEE, 2023: 8859-8864.

HAO Fei, GUO Yueming, ZHANG Chen, et al. Blockchain=better food? The adoption of blockchain technology in food supply chain [J]. International Journal of Contemporary Hospitality Management, 2024.(2024-02-09)[2024-06-06]. https://doi.org/10.1108/IJCHM-06-2023-0752.

牛淑芬, 陈俐霞, 李文婷, 等. 基于区块链的电子病历数据共享方案 [J]. 自动化学报, 2022, 48(8): 2028-2038.

NIU Shufen, CHEN Lixia, LI Wenting, et al. Electronic medical record data sharing scheme based on blockchain [J]. Acta Automatica Sinica, 2022, 48(8): 2028-2038.

CHOI T M, SIQIN T. Blockchain in logistics and production from blockchain 1.0 to blockchain 5.0: an intra-inter-organizational framework [J]. Transportation Research: Part E Logistics and Transportation Review, 2022, 160: 102653.

NAIDU P R, BOLLA D R, G P, et al. E-voting system using blockchain and homomorphic encryption [C]//2022 IEEE 2nd Mysore Sub Section International Conference. Piscataway, NJ, USA: IEEE, 2022: 1-5.

陈思光, 王倩, 张海君, 等. 区块链赋能物联网中联合资源分配与控制的智能计算迁移研究 [J]. 计算机学报, 2022, 45(3): 472-484.

CHEN Siguang, WANG Qian, ZHANG Haijun, et al. Resource allocation and control co-aware smart computation offloading for blockchain-enabled IoT [J]. Chinese Journal of Computers, 2022, 45(3): 472-484.

李程, 袁勇, 郑志勇, 等. 基于区块链的联邦学习:模型、方法与应用 [J]. 自动化学报, 2024, 50(6): 1059-1085.

LI Cheng, YUAN Yong, ZHENG Zhiyong, et al. Blockchain-enabled federated learning: models, methods and applications [J]. Acta Automatica Sinica, 2024, 50(6): 1059-1085.

CHEN Nan, KANG Wenxuan, KANG Ningxuan, et al. Order processing task allocation and scheduling for E-order fulfilment [J]. International Journal of Production Research, 2022, 60(13): 4253-4267.

ISLAM S, AMIN S H, WARDLEY L J. Machine learning and optimization models for supplier selection and order allocation planning [J]. International Journal of Production Economics, 2021, 242: 108315.

DI PASQUALE V, IANNONE R, NENNI M E, et al. A model for green order quantity allocation in a collaborative supply chain [J]. Journal of Cleaner Production, 2023, 396: 136476.

WANG Jian, MIAO Huimin, YU Mingzhu. Interdependent order allocation in the two-echelon competitive and cooperative supply chain [J]. International Journal of Production Research, 2019, 57(4): 1190-1213.

刘军, 任建华, 冯硕. 一种规模化混杂生产线缓冲区容量优化分配技术 [J]. 自动化学报, 2023, 49(5): 1073-1088.

LIU Jun, REN Jianhua, FENG Shuo. Optimal allocation technology for buffer capacity of large-scale hybrid production lines [J]. Acta Automatica Sinica, 2023, 49(5): 1073-1088.

苏裕林, 刘浩, 苏琦, 等. 统一计算架构下的装配精度并行计算模型 [J]. 西安交通大学学报, 2023, 57(6): 105-114.

SU Yulin, LIU Hao, SU Qi, et al. Parallel computing model for assembly accuracy with compute unified device architecture [J]. Journal of Xi'an Jiaotong University, 2023, 57(6): 105-114.

ZHAO Hantao, GUO Tan, TONG Weiping, et al. PaCS: a parallel computation framework for field-based crowd simulation [J]. IEEE Transactions on Intelligent Transportation Systems, 2023, 24(11): 12659-12670.[21] 肖兮, 刘闯, 何锋, 等. 面向流体机械仿真的层次化并行计算模型 [J]. 西安交通大学学报, 2019, 53(2): 121-127.

XIAO Xi, LIU Chuang, HE Feng, et al. Design and implementation of a parallel computing model for fluid machinery [J]. Journal of Xi'an Jiaotong University, 2019, 53(2): 121-127.

吴磊. 面向共享制造的智能合约设计方法研究 [D]. 西安: 长安大学, 2023.

DEB K, JAIN H. An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach: part Ⅰ solving problems with box constraints [J]. IEEE Transactions on Evolutionary Computation, 2014, 18(4): 577-601.

徐宜刚, 陈勇, 王宸, 等. 改进NSGA-Ⅲ求解高维多目标绿色柔性作业车间调度问题 [J/OL]. 系统仿真学报.(2023-09-18)[2024-06-06]. https://doi.org/10.16182/j.issn1004731x.joss.23-0694.

XU Yigang, CHEN Yong, WANG Chen, et al. Improving NSGA-Ⅲ algorithm for solving many-objective green flexible job shop scheduling problem [J/OL]. Journal of System Simulation.(2023-09-18)[2024-06-06]. https://doi.org/10.16182/j.issn1004731x.joss.23-0694.

柴依扬, 张乐乐, 窦伟元, 等. 基于并行NSGA-Ⅲ算法的高速列车车体侧墙结构高维多目标优化 [J]. 机械工程学报, 2024, 60(6): 321-333.

CHAI Yiyang, ZHANG Lele, DOU Weiyuan, et al. Parallel NSGA-Ⅲ based multi-objective optimization for side wallsection size of high-speed train car-body [J]. Journal of Mechanical Engineering, 2024, 60(6): 321-333.

杨文晋, 李永东, 王洪广, 等. 采用多准则决策分析的高功率微波源多目标优化设计 [J]. 西安交通大学学报, 2023, 57(6): 74-85.

YANG Wenjin, LI Yongdong, WANG Hongguang, et al. Multi-objective optimization design of high-power microwave source based on multi-criteria decision making [J]. Journal of Xi'an Jiaotong University, 2023, 57(6): 74-85.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Research on the Electrohydrodynamic Effects of Ionic Liquid-Modified Fuels

Energy Efficiency Optimization of the Cryogenic Air Separation Process for Electronic-Grade Ultra Pure Nitrogen

Windage Loss and Flow Characteristics in Impeller Back Gaps of sCO2 Radial Inflow Turbines

Numerical Simulation of Heat-Moisture Barrier Performance of a Horizontal Air Curtain in Cold Storage

Mechanism and Optimal Control Strategy for Hysteresis in Rapid Dehumidification Response of Indirect Thermal Systems in Electric Vehicles

Related Author

No data

Related Institution

No data

⁰