Machine Learning • Logistics
Apex: Global Logistics Coordinator
A machine learning navigation routing engine coordinating over 15,000 active delivery vehicles and optimizing fuel consumption.
Key Performance Metrics
$4.2M/yrFuel Expenses Saved
98.9%On-Time Delivery
15kActive Routes Scheduled
The Challenge
Apex Cargo Group was experiencing extreme fuel price volatility. Delivery routes planned with standard mapping software failed to account for commercial vehicle profiles, dynamic traffic jams, and drop-off time slots, wasting millions annually.
Our Engineering Solution
We constructed a multi-agent reinforcement learning algorithm that runs on AWS SageMaker. The system ingests live vehicle GPS updates, local weather reports, and traffic speeds, calculating optimal route re-dispatching instructions on the fly.
Business Outcomes
Optimized dispatch routes dynamically, reducing empty driving miles by 18%.
Improved overall fleet punctuality rate to 98.9%.
Allowed automated scheduling of complex multi-stop routes in under 3 minutes.
Integration Stack
PythonTensorFlowKubernetesAWS SageMakerGoRedisGoogle Cloud Maps