Overview

Faster routes. Leaner inventory. Fewer surprises-powered by AI. In AI in Logistics: Streamlining Supply Chains with Intelligence, you'll learn how to turn data into decisive action across planning, warehousing, transportation, and last-mile delivery. This practical guide shows exactly how to apply machine learning, optimization, and real-time analytics to cut costs, raise service levels, and build resilient, transparent supply chains. Inside, you'll discover how to: Build demand forecasting pipelines that reduce stockouts and overstock with explainable predictions. Implement inventory optimization (safety stock, reorder points, multi-echelon) aligned to service targets and variability. Deploy routing & dispatch intelligence: dynamic routing, time-windowed VRP, ETA prediction, and last-mile orchestration. Optimize warehouse operations with slotting, wave/pick path planning, labor planning, and vision-based QC. Integrate IoT/telematics for cold-chain integrity, asset tracking, and real-time exception management. Use digital twins for scenario testing: network design, hub placement, and what-if disruption planning. Operationalize with MLOps: data quality checks, drift monitoring, A/B rollouts, and KPI dashboards that finance trusts. Strengthen risk & resilience via anomaly detection, delay prediction, and proactive mitigation playbooks. With step-by-step workflows, model patterns, and case studies, this book equips logistics leaders, data teams, and operators to ship AI that performs-not just in pilots, but in production. Who This Book Is For Supply chain & logistics leaders driving cost and service improvements Data scientists/engineers productizing forecasting, routing, and optimization Operations managers modernizing WMS/TMS/ERP with real-time intelligence Consultants and practitioners building resilient, data-driven networks Deliver more with less-by making every mile, pallet, and minute intelligent.

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