Logistics Supply Chain Using Blockchain-Based Cyber-Physical System and K-Means Algorithm

Paul Livingston*
University of Groningen, Groningen, The Netherlands.
Periodicity:December - February'2021
DOI : https://doi.org/10.26634/jit.10.1.18405

Abstract

Due to the revolutionary nature of the blockchain, it is now used not only in the financial and banking sectors. Currently, logistics management is very essential, since it plays a role to guarantee the most effective possible operation of the shipping, delivery, and supply chain management systems and processes. The blockchain makes it possible to communicate in a seamless and integrated manner. Current use cases are mostly concerned with bringing out all data together from many sources. It is possible to establish information openness, traceability, and tamper resistance, and consumers' data security is achieved effectively through blockchain by Cyber-Physical System (CPS). The security, automation, and intelligence of logistics business service transactions have all been compromised as a result of this. This Cyber-Physical System benefits in production planning, control, and monitoring are discussed in this paper, as well as the K-means algorithm for order allocation and how it may best serve customers' requirements.

Keywords

Blockchain, Cyber-Physical System, K-Means Algorithm, Intelligent Logistics.

How to Cite this Article?

Livingston, P. (2021). Logistics Supply Chain Using Blockchain-Based Cyber-Physical System and K-Means Algorithm. i-manager's Journal on Information Technology, 9(4), 10-16. https://doi.org/10.26634/jit.10.1.18405

References

[1]. Casino, F., Kanakaris, V., Dasaklis, T. K., Moschuris, S., Stachtiaris, S., Pagoni, M., & Rachaniotis, N. P. (2020). Blockchain-based food supply chain traceability: A case study in the dairy sector. International Journal of Production Research, 59(19), 2728-5770. https://doi.org/ 10.1080/00207543.2020.1789238
[2]. Francisco, K., & Swanson, D. (2018). The supply chain has no clothes: Technology adoption of blockchain for supply chain transparency. Logistics, 2(1), 21-26.
[3]. Kanodia, M. (2021, February 9). Blockchain: An Overview. iNeuron. Retrieved from https://inblog.in/Block chain-An-Overview-YUFVGhvfRv
[4]. Korpela, K., Hallikas, J., & Dahlberg, T. (2017, January). Digital supply chain transformation toward th blockchain integration. In Proceedings of the 50 Hawaii International Conference on System Sciences.
[5]. Latif, R. M. A., Farhan, M., Rizwan, O., Hussain, M., Jabbar, S., & Khalid, S. (2021). Retail level blockchain transformation for product supply chain using truffle development platform. Cluster Computing, 24(1), 1-16.
[6]. MacQueen, J. (1967, June). Some methods for classification and analysis of multivariate observations. In Proceedings of the fifth Berkeley symposium on mathematical statistics and probability, 1(14), 281-297.
[7]. Marco, I., & Lakhani, K. R. (2017). The truth about blockchain. Harvard Business Review, 95(1), 118-127.
[8]. Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. Decentralized Business Review, 21260.
[9]. Thada, A., Kapur, U. K., Gazali, S., Sachdeva, N., & Shridevi, S. (2019). Custom block chain based cyber physical system for solid waste management. In Procedia Computer Science, 165, 41-49. https://doi.org/10.1016/ j.procs.2020.01.068
[10]. TMS. (n.d.). Transportation Management Systems (TMS) and Intelligent LogisticsOne Network Enterprises. Retrieved from https://www.onenetwork.com/supplychain- management-solutions/intelligent-logistics/trans portation-management-systems-tms/
[11]. Tribis, Y., El Bouchti, A., & Bouayad, H. (2018). Supply chain management based on blockchain: A systematic mapping study. In MATEC Web of Conferences, EDP Sciences.
[12]. Wang, J., Lim, M. K., Zhan, Y., & Wang, X. (2020). An intelligent logistics service system for enhancing dispatching operations in an IoT environment. Transportation Research Part E: Logistics and Transportation Review, 135, 1-12. https://doi.org/10.1016/j.tre.2020.101886
[13]. Yang, C. S., & Lirn, T. C. (2017). Revisiting the resource-based view on logistics performance in the shipping industry. International Journal of Physical Distribution & Logistics Management, 47, 884–905. https://doi.org/10.1108/IJPDLM-05-2017-0184
[14]. Zhang, S., Bi, C., & Zhang, M. (2021). Logistics service supply chain order allocation mixed K-Means and Qos matching. In Procedia Computer Science, 188, 121- 129. https://doi.org/10.1016/j.procs.2021.05.060
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