Analysis of joint distribution and intelligent express cabinet location based on K-means clustering algorithm

Xuehua Cheng; Xiaofeng Cao

doi:10.1117/12.2691808

23 August 2023 Analysis of joint distribution and intelligent express cabinet location based on K-means clustering algorithm

Xuehua Cheng, Xiaofeng Cao

Author Affiliations +

Proceedings Volume 12784, Second International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2023); 127841T (2023) https://doi.org/10.1117/12.2691808
Event: 2023 2nd International Conference on Applied Statistics, Computational Mathematics and Software Engineering (ASCMSE 2023), 2023, Kaifeng, China

Abstract

In recent years, with the rapid development of the e-commerce industry, it is no longer an empty talk to buy everything at home. The role of the express delivery industry in this process is very important. Reasonable selection of express outlets can reduce their operating costs. The widespread use of intelligent express cabinets can effectively improve the service quality of the last kilometer of express delivery, and also improve the delivery efficiency. Through the study of the joint distribution model, this paper compares the third-party joint distribution model with the joint distribution model of the alliance enterprises. The conclusion is that the integration of some outlets can effectively reduce costs. Then, the K-means clustering model is established to analyze the location selection of the outlets, and the initial clustering center and clustering results are obtained. On this basis, the optimization operation is carried out to obtain the optimal location of the express outlet center, and the number and location of the intelligent express cabinet are analyzed.

Citation Download Citation

Xuehua Cheng and Xiaofeng Cao "Analysis of joint distribution and intelligent express cabinet location based on K-means clustering algorithm", Proc. SPIE 12784, Second International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2023), 127841T (23 August 2023); https://doi.org/10.1117/12.2691808

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