Circular logistics and reverse-flow orchestration THEME 2 Optimizing supply chain logistics using quantum computingEXTERNAL LOGISTICS | CASE STUDY Port of Los Angeles Challenge Solution Impact Rising cargo volumes strained operations at the Port of Los Angeles, with long truck waits, inefficient crane movements and underused assets exposing the limits of rule-based scheduling.A hybrid quantum computing-based optimization engine was deployed to address large-scale, combinatorial scheduling challenges. The solution evaluated a vastly expanded solution space, simulating over 100,000 cargo- handling scenarios. By dynamically optimizing truck-to-crane assignments under real-time constraints, the system generated near-optimal schedules that classical methods could not efficiently achieve. The initiative delivered significant efficiency and reliability gains by optimizing terminal operations and throughput, resulting in: –40% higher crane utilization. –60% more container moves per crane. –2 hours reduction in truck wait time.Evolutions of themes Enable intelligent circular flow orchestration to maximize recovery, reuse and recycling across the logistics network. Material recovery rate Return cycle timeStructured reverse logistics — Returned goods and reusable assets tracked across collection, repair and recovery points. — AI classifies items for reuse, repair, refurbishment or recycling. — Sustainability metrics are captured for each return cycle.Intelligent circular flow planning — Visualizes material lifecycles and recovery potential end-to-end. — AI predicts return volumes and identifies the most valuable recovery paths. — Repair and recycling operations are optimized for cost and turnaround.Autonomous circular ecosystems — Forward and reverse logistics flows balance automatically with AI. — Materials circulate between partners with minimal manual coordination. — A self-sustaining circular network minimizes waste and maximizes recovery.NOW (0-2 years) NEAR (3-5 years) NEXT (5+ years) ObjectivesEXTERNAL LOGISTICS Intelligent Industrial Operations Outlook 2026 43