Intelligent route planning — fewer kilometres, more deliveries
Automatically optimised routes for every driver. Multi-stop, traffic ETA, cluster splitting for parallel drivers — so every tour is more efficient than manual planning.
Route planning for delivery services means an algorithm (Travelling Salesman Problem heuristic) calculates the optimal order and route for all open deliveries — taking into account real-time traffic, time windows and vehicle capacity. This saves fuel, reduces driving time and lowers late deliveries.
Multi-stop TSP optimisation
The routing algorithm calculates the most efficient order for all stops on a tour — not the nearest address first, but the globally optimal route. With 8 stops there are 40,320 possible orderings; the algorithm finds the shortest in milliseconds. Typical efficiency gain over intuitive planning: 20–35% fewer total kilometres per tour.
Cluster splitting: coordinating multiple drivers efficiently
When 5 drivers are on the road simultaneously with 20 delivery jobs pending, the dispatch algorithm distributes jobs as geographic clusters. Driver 1 gets jobs in the north-west, driver 2 in the south-east — avoiding route crossings. Cluster size is automatically calculated based on driver capacity and distance. No manual splitting.
Real-time traffic ETA and dynamic adjustment
ETA is calculated from real traffic, not average road speeds. Traffic jam on the main route? The app automatically suggests an alternative route and updates ETA. New order comes in while driver is en route? The algorithm checks whether the new job can be added without a major detour and suggests an updated route.
Meeting time window requirements
Some customers want delivery between 12:00 and 13:00. The algorithm plans time-window jobs as hard constraints: the stop is scheduled so the driver arrives within the window. If no driver can meet the time window without conflict, the dispatcher receives a warning — before the order is confirmed.
Return timing and capacity planning
The algorithm also calculates the return: when will the driver be back at base and ready for the next tour? This is important for shift planning — you know when each driver will be available again. Vehicle capacity (number of orders or weight) is factored in: a driver never takes more jobs than they can transport.
Route planning in numbers
Shorter routes
TSP optimisation typically reduces total distance by 20–35% compared to manual planning.
Calculation time
Route for 8 stops calculated in milliseconds — no waiting.
Adjustment
New orders are automatically added to active tours.
Common questions about route planning
Can the driver manually change the suggested order?
Yes. The driver sees the optimised order in the app and can change it by drag-and-drop. The system shows how much longer the alternative route is. Local knowledge from the driver can sometimes beat the automatic optimisation.
Are vehicle types considered in route planning?
Yes. Bicycles, mopeds and cars can be set as vehicle types. The algorithm calculates routes taking into account permitted roads and capacity limits.
What happens when the algorithm can't meet a time window?
The dispatcher receives a warning: 'Time window for job #178 cannot be met.' They can then decide manually: relax the time window, assign another driver or notify the customer. The system never silently overrides time window conflicts.