Name: AI Route Optimization Lab
Author: MySimulator

Re-routing policy

Re-routing aggressiveness: 50%

This case study models a 30-stop delivery route re-optimized mid-day as new orders and traffic conditions arrive. More aggressive re-routing saves fuel and time by continuously re-sequencing stops, but each re-route disrupts drivers who had already planned around the previous sequence.

Day outcome

Total distance driven—

Re-routes issued—

Fuel cost saved—

Delivery route (yellow = current planned sequence)