Resource scheduling in cloud manufacturing system based on double blockchain structure

被引：0

作者：

Li F. ^{[1
]}

Cheng Y. ^{[1
]}

机构：

[1] School of Business, University of Shanghai for Science and Technology, Shanghai

来源：

Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2023年 / 29卷 / 11期

关键词：

blockchain; cloud manufacturing; fast elitist non-dominated sorting genetic algorithm; multi-objective; resource scheduling;

D O I：

10.13196/j.cims.2021.0454

中图分类号：

学科分类号：

摘要：

To improve the trust degree and resource scheduling efficiency among the participants in the cloud manufacturing system, explore the cloud manufacturing system based on the double blockchain structure was studied. The application of blockchain technology in the cloud manufacturing system was analyzed, and the business processes on the public chain of enterprise information and the federated chain of manufacturing resources were designed. The resource scheduling algorithm was written in the smart contract of the manufacturing resource chain to perform resource scheduling automatically. A multi-objective resource scheduling model considering innovation and matching was established. The fast elitist Non-Dominated Sorting Genetic Algorithm (NSGA- II) was used to solve the model. The effectiveness of the proposed double-chain structure and resource scheduling model was verified with contrast experiments. The results showed that the manufacturing resource scheduling had a better set of non-dominated solutions and the resource scheduling speed was improved after the mutual trust among the participating nodes in the cloud manufacturing system based on the double-chain structure. © 2023 CIMS. All rights reserved.

引用

页码：3786 / 3799

页数：13

共 24 条

[1]

XIAO Yingymg, LI Bohu, HOU Baocun, Et al., Planning and scheduling technology review of supply chain management in smart manufacturing cloud[j], Computer Integrated Manufacturing Systems, 22, 7, pp. 1619-1635, (2016)

[2]

LI Bohu, ZHANG Lin, WANG Shilong, Et al., Cloud manufacturing: A new service-oriented manufacturing model [J], Computer Integrated Manufacturing Systems, 16, 1, pp. 1-7, (2010)

[3]

WANG Shllong, SONG Wenyan, KANG Ling, Et al., Manufacturing resource allocation based on cloud manufacturing [J], Computer Integrated Manufacturing Systems, 18, 7, pp. 1396-1405, (2012)

[4]

TAO Fel, ZHANG Lin, GUO Hua, Typical characteristics of cloud manufacturing and several key issues of cloud service composition [J], Computer Integrated Manufacturing Systems, 17, 3, pp. 477-486, (2011)

[5]

LI Qiang, RU Ke, LIU Jiliang, Et al., Interactive cloud manufacturing model for mass personalization[j], China Mechanical Engineering, 31, 7, pp. 788-796, (2020)

[6]

WANG Ping, XIAO Han, PAN Yanhua, Cloud manufacturing resource service composition based on bi-level programming [J], Computer Integrated Manufacturing Systems, 28, 1, pp. 51-58, (2022)

[7]

Multiobjective real-time scheduling of tasks in cloud manufacturing with genetic algorithm[J], Mathematical Problems in Engineering, 2021, pp. 1-10, (2021)

[8]

CAO Wenying, JIA Guozhu, KONG Jili, Et al., Cloud manufacturing resource scheduling based on trust between enterpri-ses, Industrial Engineering and Management, 25, 4, (2020)

[9]

LI Yongxiang, YAO Xifan, LIU Mln, Cloud manufacturing service composition optimization based on reliability andcredi-bility analysis [J], Computer Integrated Manufacturing Systems, 27, 6, pp. 1780-1798, (2021)

[10]

YUAN Wei, GUO Wei, WANG Lei, Et al., Bl-layer optimization method of service composition for small batch customized products under cloud manufacturing, Computer Integrated Manufacturing Systems, pp. 1-24, (2022)

← 1 2 3 →