Optimizing Supply Chain Logistics Using AI-Driven Predictive Analytics
Abstract
This Paper explores the integration of AI-driven predictive analytics in supply chain logistics to enhance efficiency and reduce costs. By utilizing machine learning algorithms to analyze historical data and predict future demand, companies can optimize inventory levels, streamline transportation routes, and minimize delays. The chapter provides case studies of successful implementations and discusses the potential challenges and solutions in adopting predictive analytics for logistics optimization.
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