Proceedings of the 2024 3rd International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2024)

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Research on the Optimization of Picking Path Considering the Minimization of Goods Damage Cost

Authors
Jiaxing Lu1, Hui Zhang1, Zhenzhuo Zhang1, Xiaodong Li2, *, Jia Liu3
1College of Automation and Electrical Engineering, Linyi University, Linyi, Shandong, China
2Logistics College, Linyi University, Linyi, Shandong, China
3Shandong Modern Logistics Technology Industry Research Institute Co, Ltd, Linyi, Shandong, China
*Corresponding author. Email: wlxy@lyu.edu.cn
Corresponding Author
Xiaodong Li
Available Online 31 August 2024.
DOI
10.2991/978-94-6463-490-7_54How to use a DOI?
Keywords
MATLAB; improved ant colony algorithm; path optimization; goods damage cost
Abstract

Along with the vigorous development of e-commerce platforms, all kinds of goods with different values appear on various platforms, with the value of goods exhibiting a considerable gap. In this regard, the packaging damage of goods has consistently been an inevitable problem during the picking process. Moreover, customers put forward increasingly high requirements for the integrity of goods. Particularly, the cost caused by the breakage of valuables is usually hundreds of times that of items with lower prices. To address the foregoing challenges, this paper proposes a mathematical model of the multi-vehicle picking path considering the goods damage cost, leveraging an improved ant colony algorithm to solve it. In this foundation, this research further implements relevant simulation experiments through MATLAB. The research findings reveal that the vulnerability value of goods in the second half of the path within the scale of 100 is obviously higher than that in the first half, further verifying the validity of the model and algorithm. Simply put, the methodology proposed in this research improves both the picking efficiency and customer satisfaction.

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 Artificial Intelligence, Internet and Digital Economy (ICAID 2024)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
31 August 2024
ISBN
978-94-6463-490-7
ISSN
2589-4919
DOI
10.2991/978-94-6463-490-7_54How to use a DOI?
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.

Cite this article

risenwbib
TY  - CONF
AU  - Jiaxing Lu
AU  - Hui Zhang
AU  - Zhenzhuo Zhang
AU  - Xiaodong Li
AU  - Jia Liu
PY  - 2024
DA  - 2024/08/31
TI  - Research on the Optimization of Picking Path Considering the Minimization of Goods Damage Cost
BT  - Proceedings of the 2024 3rd International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2024)
PB  - Atlantis Press
SP  - 497
EP  - 510
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-490-7_54
DO  - 10.2991/978-94-6463-490-7_54
ID  - Lu2024
ER  -