Algorithm in E-commerce logistics
Abstract
First, the logistics information for e-commerce is explained. A detailed analysis is also done on the block chain technology, cryptography technology, block chain consensus algorithm, block chain application scenarios, and other relevant technologies. In the end, a block chain model for tracking logistical information in real-time for e-commerce is developed. It is discovered that data will only be saved on the chain when more than 51% of the distributed system's nodes certify that the data are accurate. If not, there would be no impact on the chain's data. Finally, the model description and hypothesis of real-time tracking of e-commerce logistics information based on block chain technology are verified to provide guarantee for improving real-time tracking of e-commerce logistics information. provide defence against unauthorized modifications or tampering. We validate the proposed model and assumptions at to show how well they work to improve the real-time tracking capabilities of e-commerce logistics information systems. The end This study is a first step toward integrating blockchain technology to improve the dependability and effectiveness of e-commerce logistics operations. The demonstrated effectiveness of the suggested model and its underlying assumptions presents a viable approach to augmenting the e-commerce logistics systems' real-time tracking capacities. This study lays the foundation for future developments in the area by integrating blockchain technology as a first step toward improving the reliability and effectiveness of e-commerce logistics operations
References
Yang D, Wu P. E-commerce logistics path optimization based on a hybrid genetic algorithm. Complexity. 2021 Mar 22; 2021:1-0.
Feng Z. Constructing rural e-commerce logistics model based on ant colony algorithm and artificial intelligence method. Soft Computing. 2020 Jun;24(11):7937-46.
He X, Meng S, Liang J. Analysis of cross-border E-Commerce logistics model based on embedded system and genetic algorithm. Microprocessors and Microsystems. 2021 Apr 1; 82:103827.
Zhang X, Bartol KM. Linking empowering leadership and employee creativity: The influence of psychological empowerment, intrinsic motivation, and creative process engagement. Academy of management journal. 2010 Feb;53(1):107-28.
Lindblom A, Kajalo S, Mitronen L. Exploring the links between ethical leadership, customer orientation and employee outcomes in the context of retailing. Management Decision. 2015 Aug 17;53(7):1642-58.
Rintamäki T, Mitronen L. Creating information-based customer value with service systems in retailing. Service Systems Science. 2015:145-62.
Han L, Wang DZ, Lo HK, Zhu C, Cai X. Discrete-time day-to-day dynamic congestion pricing scheme considering multiple equilibria. Transportation Research Part B: Methodological. 2017 Oct 1; 104:1-6.
Wollenburg JE, Raitzsch M, Tiedemann R. Novel high-pressure culture experiments on deep-sea benthic foraminifera—Evidence for methane seepage-related δ13C of Cibicides wuellerstorfi. Marine Micropaleontology. 2015 May 1; 117:47-64.
Galipoglu E, Kotzab H, Teller C, Yumurtaci Hüseyinoglu IÖ, Pöppelbuß J. Omni-channel retailing research–state of the art and intellectual foundation. International Journal of Physical Distribution & Logistics Management. 2018 May 1;48(4):365-90.
Xianglian C, Hua L. Research on e-commerce logistics system informationization in chain. Procedia-social and behavioral sciences. 2013 Nov 6; 96:838-43.
