Intelligent Logistics Path Optimization and Real-Time Dispatching System Design Based on Big Data Analysis

Shumin Zhang; Zheng Yang; Yang Zhang

doi:10.2991/978-94-6463-447-1_13

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Intelligent Logistics Path Optimization and Real-Time Dispatching System Design Based on Big Data Analysis

Authors

Shumin Zhang¹^{, *}, Zheng Yang², Yang Zhang³

¹School of Business Administration, Liaoning Technical University, Huludao, 125105, Liaoning, China

²College of Environmental Science and Engineering, Liaoning Technical University, Fuxing, 123000, Liaoning, China

³School of Business Administration, Liaoning Technical University, Huludao, 125105, Liaoning, China

^*Corresponding author. Email: 2314972030@qq.com

Corresponding Author

Shumin Zhang

Available Online 14 July 2024.

DOI: 10.2991/978-94-6463-447-1_13 How to use a DOI?
Keywords: Big Data Analysis; Intelligent Logistics; Route Optimization; Real-Time Scheduling; Order Allocation Model
Abstract: The advancement of intelligent technology has brought the technological foundation for path optimization and real-time scheduling systems to the logistics industry, enabling more accurate and efficient order delivery. In order to further optimize the working conditions of intelligent logistics, this article proposes the technical tool of big data analysis. Moreover, this article also conducted a comparative experiment based on the method in this article and other mainstream methods at the end. In the comparative experiment on delivery time for users in a specific area, the average delivery time of the former was 10.82h, while the average delivery time of the latter was 14.81h. The obvious experimental gap fully reflects that big data analysis technology can well carry out intelligent logistics path optimization and real-time dispatch system design.
Copyright: © 2024 The Author(s)
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the 2024 3rd International Conference on Engineering Management and Information Science (EMIS 2024)
Series: Advances in Computer Science Research
Publication Date: 14 July 2024
ISBN: 10.2991/978-94-6463-447-1_13
ISSN: 2352-538X
DOI: 10.2991/978-94-6463-447-1_13 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Shumin Zhang
AU  - Zheng Yang
AU  - Yang Zhang
PY  - 2024
DA  - 2024/07/14
TI  - Intelligent Logistics Path Optimization and Real-Time Dispatching System Design Based on Big Data Analysis
BT  - Proceedings of the 2024 3rd International Conference on Engineering Management and Information Science (EMIS 2024)
PB  - Atlantis Press
SP  - 107
EP  - 114
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-447-1_13
DO  - 10.2991/978-94-6463-447-1_13
ID  - Zhang2024
ER  -

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