E-commerce logistics 4.0 network location and path planning algorithm based on DPC and D-NSPSO

The development of e-commerce has brought the public into the era of e-commerce logistics 4.0. Therefore, optimizing logistics network location and path planning is important to improve logistics efficiency and reduce operating costs. To deal with the increasingly complex market demand and the changing distribution environment, the diversity enhancement mechanism and neighborhood search strategy are introduced into the particle swarm optimization algorithm. This optimized algorithm is combined with the density peak clustering algorithm. Then, the e-commerce logistics network location and path planning algorithm is proposed. The optimal path on the grid map only produced 11 inflection points and passed 24 grids. It was the best in the comparison model. Finally, the total route length in modeling and testing was 32.51 km, the average loading rate was 97.85%, the total cost was 668.18 ¥, and the calculation time was 25.34s. The proposed model performs well in many key performance indicators, which can realize the efficient operation of logistics network. The research aims to provide new ideas and methods for network location and path planning of e-commerce logistics 4.0, which has theoretical and practical application value.

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Publication Details

Journal
Journal of Computational Methods in Sciences and Engineering
Published
2025-07-19
DOI
https://doi.org/10.1177/14727978251361537
Primary Topic
E-commerce and Technology Innovations
Type
article
Field-Weighted Citation Impact
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article

E-commerce logistics 4.0 network location and path planning algorithm based on DPC and D-NSPSO

Journal of Computational Methods in Sciences and Engineering
E-commerce and Technology Innovations
article

E-commerce logistics 4.0 network location and path planning algorithm based on DPC and D-NSPSO

article en

Abstract

The development of e-commerce has brought the public into the era of e-commerce logistics 4.0. Therefore, optimizing logistics network location and path planning is important to improve logistics efficiency and reduce operating costs. To deal with the increasingly complex market demand and the changing distribution environment, the diversity enhancement mechanism and neighborhood search strategy are introduced into the particle swarm optimization algorithm. This optimized algorithm is combined with the density peak clustering algorithm. Then, the e-commerce logistics network location and path planning algorithm is proposed. The optimal path on the grid map only produced 11 inflection points and passed 24 grids. It was the best in the comparison model. Finally, the total route length in modeling and testing was 32.51 km, the average loading rate was 97.85%, the total cost was 668.18 ¥, and the calculation time was 25.34s. The proposed model performs well in many key performance indicators, which can realize the efficient operation of logistics network. The research aims to provide new ideas and methods for network location and path planning of e-commerce logistics 4.0, which has theoretical and practical application value.

Journal of Computational Methods in Sciences and Engineering
Wuhan Polytechnic University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 34%
E-commerce and Technology Innovations
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E-commerce logistics 4.0 network location and path planning algorithm based on DPC and D-NSPSO · Journal of Computational Methods in Sciences and Engineering (2025) | TGRS Research Map | TGRS