Research on Innovation and Optimization of E-Commerce Logistics Distribution Mode Based on Big Data Analysis

  • Nan Zhao

Abstract

With the rapid development of e-commerce in China, logistics has gradually become a bottleneck restricting its development.However, to solve the problem of a long time to find the optimal path existing in the traditional e-commerce logistics distribution path optimization algorithm, an optimization algorithm of e-commerce logistics distribution path under the background of big data was designed. First of all, the clustering algorithm is used to divide the logistics distribution area. Secondly, the multi-objective function of logistics distribution path optimization is established by weight index, time index, customer importance index, time window index, as well as total path index.Finally, the weight of the distribution target is set, and the optimal distribution path in the objective function is found according to the different needs of e-commerce logistics, aiming to complete the optimization of the e-commerce logisticsdistributionpath.The experimental comparison results indicate that the time to find an optimal path of the e-commerce logistics distribution pathoptimization algorithm designed under the background of big data is shorter than that of the traditional algorithm, and it can reduce the e-commerce logistics distribution time, thus achieving the innovation of e-commerce logistics service. Therefore, it has a certain practical application significance.

Published
2021-05-17
How to Cite
Nan Zhao. (2021). Research on Innovation and Optimization of E-Commerce Logistics Distribution Mode Based on Big Data Analysis. Design Engineering, 796 - 807. Retrieved from http://www.thedesignengineering.com/index.php/DE/article/view/1592
Section
Articles