Logistics & Route Optimization

AI plans routes for robots, trucks, or inbound parts movements to reduce congestion and unnecessary travel.

Business impact

• miles traveled — Kroger reported an initial test result showing about a 3–8% reduction in miles.

Data requirements

• robot movement data (tabular) — Used to coordinate warehouse robot paths.
• truck routing data (tabular) — Used to support distribution-center-to-store routing.
• employee bus-travel data (tabular) — Used in the Rockwell case to optimize routes across plants.
• supply-chain disruption information (tabular) — Used to model alternate ways to recover and reroute components.

AI methods and techniques

• deep learning — Used by 84.51° to support truck routing decisions.
• path planning — Used by Amazon’s DeepFleet to plan paths for warehouse robots.
• routing optimization — Used to choose better truck routes and reroute components when conditions change.
• control tower support — Used at Renault to support inbound supply-chain decisions and alternative rerouting.

AI models and model families

DeepFleet foundation model

Industries

Real-world evidence

4 documented case studies on record.

Companies using this: Amazon, Kroger, Renault, Rockwell Automation.