AI Route Optimisation for Delivery Planning
Logistics
Overview
Logistics companies managing hundreds of daily deliveries across distributed geographies face enormous inefficiency through manual route planning. VINSINFO built an AI planning engine based on Vehicle Routing Problem (VRP) optimisation that generates optimal multi-stop, multi-truck delivery plans in seconds — replacing hours of manual effort and eliminating costly routing inefficiencies.
Fuel cost reduction
15-
0
%
On-time delivery improvement
0
%
Fleet size reduction
10-
0
%
Challenge
- Multiple delivery destinations spread across large geographic areas
- Truck capacity and time-window constraints difficult to balance manually
- Inefficient routes increasing fuel consumption and vehicle wear
- Manual planning consuming 3–4 hours per day
- Inability to adapt in real time to delays or last-minute orders
- Poor fleet utilisation and increased transportation costs
Solution
- AI engine ingests warehouse location, destinations, deadlines, and capacity
- Distance matrix built using live map APIs and geographic coordinates
- VRP optimisation evaluates combinations against distance, capacity, and time
- Routes minimise total mileage, fuel use, and fleet size simultaneously
- Interactive map visualisation with per-truck delivery sequences
- Scalable to hundreds or thousands of deliveries per run
Impact
Fuel consumption reduced by 15–25% through optimised routing
On-time delivery rate improved by 30%
Fleet size requirements reduced by 10–20% through better utilisation
Planning time cut from hours to seconds
Overall transportation costs lowered by 20–30%
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