Abstract—The advent of Machine Learning (ML), Artificial Intelligence (AI), and the Internet of Things (IoT) has revolutionized Supply Chain Management (SCM), enabling enhanced data-driven decision-making and real-time optimization. This paper presents an advanced and comprehensive mathematical model integrating ML, AI, and IoT technologies within SCM. Building upon recent advancements in inventory control optimization techniques, we develop a multi-echelon supply chain model incorporating predictive analytics and real-time data flows. The model’s assumption, notation, formulation, and solution are thoroughly discussed. Graphical representations illustrate the mathematical model and its solutions. Sensitivity analysis demonstrates the model’s robustness under varying parameters. Numerical examples validate the theoretical findings, highlighting optimization potentials in modern SCM practices.
 
Keywords—supply chain management, machine learning, artificial intelligence, internet of things, mathematical modeling, optimization, sensitivity analysis
Cite: Atma Nand, Shiva Nand, and Abhiral Gahlot, "Integration of Machine Learning, Artificial Intelligence, and IoT in Supply Chain Management: An Advanced Mathematical Modeling Approach," Journal of Advanced Management Science, Vol. 13, No. 1, pp. 35-40, 2025.