In today's fast-moving markets, supply chains must be smarter, faster, and more resilient than ever. AI for Supply Chain Optimization shows you how predictive models and machine learning can transform logistics, reduce costs, and improve decision-making across procurement, inventory, transportation, and demand planning.
This book takes you step by step from understanding supply chain data to building and deploying AI models that deliver real business impact. You'll learn how to forecast demand accurately, optimize routes, predict supplier risks, manage inventory dynamically, and detect anomalies before they disrupt operations. The guide covers practical techniques including regression models, time-series forecasting, reinforcement learning, and optimization algorithms, all applied to real-world supply chain problems.
With hands-on projects in Python using scikit-learn, TensorFlow, and PyTorch, you'll gain experience building models that integrate ERP and logistics data, generate actionable insights, and improve operational efficiency. You'll also learn best practices for data preprocessing, model validation, monitoring performance, and scaling solutions in enterprise environments.
Whether you are a data scientist, operations manager, or logistics professional, this book equips you with the tools to transform supply chains with AI. Buy this book now and start applying predictive intelligence to your logistics and operations today.