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Article type: Research Article
Authors: Wang, Xiaokuna; b | Zhao, Chenxia; b | Wang, Yuana; b | Xiao, Hongc; *
Affiliations: [a] School of Economics and Management, Dalian Jiaotong University, Dalian, Liaoning, China | [b] Research Institute of the Belt and Road, Dalian Jiaotong University, Dalian, Liaoning, China | [c] School of Economics and Management, Chongqing Jiaotong University, Chongqing, China
Correspondence: [*] Corresponding author: Hong Xiao, School of Economics and Management, Chongqing Jiaotong University, Chongqing 400074, China. E-mail: [email protected].
Abstract: The logistics service transaction matching of the blockchain platform is an important part of the transaction. Firstly, the evaluation index system of the logistics service transaction satisfaction degree in the blockchain platform is constructed. According to the evaluation index of the logistics service users and providers, the actual situation of the logistics service transaction and the principle of maximizing the satisfaction degree of the logistics service users and providers, we set the expectation range of both sides and do data standardization, design the calculation method of satisfaction information amount for different expectation data types, build a multi-objective optimization model for logistics service transaction matching on blockchain platform, and seek the matching solution that makes all service users and providers the most satisfaction. Considering the large amount of data in blockchain, the concurrent design of NSGA-II algorithm based on Hadoop is carried out. Through the calculation of the example, in the matching of multi-objective optimization model of logistics service transaction matching on the blockchain platform, when the users and providers of logistics service are more satisfied about the indicators with each other, and then it gets more satisfactory matching results.
Keywords: Blockchain platform, logistics service, satisfaction, transaction matching model, NSGA-II algorithm
DOI: 10.3233/JCM-215468
Journal: Journal of Computational Methods in Sciences and Engineering, vol. 21, no. 6, pp. 1843-1855, 2021
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