Cognitive AI for Autonomous Supply Chain Disruption Management: Architecture, Implementation, and Evaluation

Authors

  • Ankit Sharma

Keywords:

Cognitive AI; Supply Chain Resilience; Autonomous Disruption Management; Reinforcement Learning; Natural Language Processing (NLP); Digital Twin Simulation; ERP Integration; Real-time Decision Systems; Anomaly Detection; Intelligent Supply Chain Automation.

Abstract

Modern supply chains are increasingly exposed to disruptions caused by geopoliticalinstability, climate change, and market volatility. This paper presents a novel cognitive AIframework designed for autonomous disruption management in complex, multi-tiered supply networks

References

• Aboutorab, H., Hussain, O. K., Saberi, M., Hussain, F. K., & Prior, D. (2024). Adaptive identification of supply chain disruptions through reinforcement learning. Expert Systems with Applications, 248, 119348.

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Published

2024-05-31

How to Cite

Ankit Sharma. (2024). Cognitive AI for Autonomous Supply Chain Disruption Management: Architecture, Implementation, and Evaluation. Journal of Computational Analysis and Applications (JoCAAA), 33(05), 3436–3459. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/4604

Issue

Vol. 33 No. 05 (2024): JOCAAA

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.