AI in Supply Chain Analytics: Adaptive Decisioning via Fuzzy Behavioral Models

• Apeksha Bhuekar

  Author

The goal of this paper is to develop intelligent agents through fuzzy logic so that they can be capable of adaptability and context awareness in a simulated operational environment. Concentrating on dynamic interactions, fuzzy inference systems help agents to adjust their behavior according to proximity, velocity, and environmental conditions. The suggested approach helps to develop adaptive and robust automated decision-making systems. These components can optimize complex multi-stakeholder systems explicitly beneficial for modern supply chain systems. The paper states that AI can be used to enhance the flexibility and reactivity of logistics and inventory management systems, offering various technical and practical contributions.

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