Vendor Transportation Management Using AI and ML

Gajendra Sahu; Pranav Pandey; Abhishek Diwan; Ayush Sahu

doi:10.2991/978-94-6463-738-0_86

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Vendor Transportation Management Using AI and ML

Authors

Gajendra Sahu¹, Pranav Pandey¹, Abhishek Diwan¹, Ayush Sahu²^{, *}

¹B. Tech. Scholar, CSE Department, SSIPMT, Raipur, Chhattisgarh, India

²Assistant Professor CSE Department SSIPMT, Raipur, Chhattisgarh, India

^*Corresponding author. Email: ayush.sahu25220@ssipmt.com

Corresponding Author

Ayush Sahu

Available Online 22 June 2025.

DOI: 10.2991/978-94-6463-738-0_86 How to use a DOI?
Keywords: Machine learning (ML); Artificial intelligence (AI); Supply chain logistics; Route optimization; Autonomous transport systems
Abstract: This study explores the transformative role of machine learning (ML) and artificial intelligence (AI) in optimizing vendor transportation management, a critical aspect of supply chain logistics. Traditional systems struggle with inefficiencies in route planning, unpredictable demand, and fluctuating operational conditions. AI-driven technologies, including real-time monitoring, predictive analytics, and route optimization algorithms, provide smarter, more adaptable solutions. By leveraging big data and the Internet of Things (IoT), ML models—both supervised and unsupervised—enhance demand forecasting, fleet management, and cost reduction while maintaining service quality. Deep learning further refines pattern recognition for improved decision-making. Case studies and simulations demonstrate significant gains in cost efficiency, delivery schedules, and resource utilization. Additionally, autonomous transport systems integrated with AI enable partial or full self-management, promoting sustainable and scalable logistics. Future research highlights the potential of hybrid AI systems combined with blockchain for secure, transparent operations, alongside innovations like drones and driverless vehicles for last-mile delivery. Aligning with Industry 4.0, this study outlines a roadmap for AI-driven vendor transportation, ensuring efficiency, sustainability, and competitiveness in modern supply chain management.
Copyright: © 2025 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 International Conference on Advances and Applications in Artificial Intelligence (ICAAAI 2025)
Series: Advances in Intelligent Systems Research
Publication Date: 22 June 2025
ISBN: 978-94-6463-738-0
ISSN: 1951-6851
DOI: 10.2991/978-94-6463-738-0_86 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  - Gajendra Sahu
AU  - Pranav Pandey
AU  - Abhishek Diwan
AU  - Ayush Sahu
PY  - 2025
DA  - 2025/06/22
TI  - Vendor Transportation Management Using AI and ML
BT  - Proceedings of the International Conference on Advances and Applications in Artificial Intelligence (ICAAAI 2025)
PB  - Atlantis Press
SP  - 1116
EP  - 1126
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-738-0_86
DO  - 10.2991/978-94-6463-738-0_86
ID  - Sahu2025
ER  -

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