Route optimisation is one of those terms that every logistics software vendor uses and few explain properly. It sounds straightforward — find the shortest path. In practice, it is considerably more complex, and the quality of the implementation determines whether it delivers real operational improvement or just a slightly reorganised version of what the dispatcher was already doing.
What Route Optimisation Is Solving
The underlying problem is called the Vehicle Routing Problem (VRP) — a classic operations research challenge. Given a set of delivery locations, a set of vehicles with defined capacities, and a set of constraints, find the assignment of locations to vehicles and the sequence of visits that minimises total distance (or time, or cost).
This is computationally difficult at scale. For a small number of deliveries and vehicles, exact solutions exist. As the number of deliveries and vehicles grows, exact solutions become computationally intractable — modern route optimisation uses heuristic algorithms that find near-optimal solutions quickly rather than searching for the mathematically perfect solution.
The Inputs That Actually Determine Route Quality
The quality of a route optimisation output is only as good as the inputs it works with. The inputs that matter most:
- Delivery location coordinates: Not just addresses, but geocoded coordinates. An address can be geocoded to the wrong point if the geocoding database is not current or the address is ambiguous.
- Time windows: Customer-specified delivery windows that constrain when each delivery can be made.
- Vehicle capacities: Weight and volume limits for each vehicle. A route that assigns more load than the vehicle can carry is not a valid route.
- Driver constraints: Maximum driving hours, break requirements, driver home location, and driver-specific restrictions.
- Historical delivery time data: How long does a delivery at this type of location typically take? Office deliveries are fast; industrial deliveries requiring goods unloading take longer.
- Real-time traffic data: For urban delivery routes where traffic congestion significantly affects transit time, real-time traffic integration improves ETA accuracy and enables dynamic re-routing.
What Route Optimisation Delivers in Practice
The efficiency improvement from route optimisation depends significantly on the baseline — how routes were being planned before, and how much inefficiency was in the previous approach.
For routes previously planned by dispatcher experience: Route optimisation applied to the same delivery set typically reduces total distance by 15 to 25% compared to experienced dispatcher planning.
For routes previously planned on paper maps or basic tools: The improvement is larger — typically 25 to 40% distance reduction.
The compounding effect: Fewer kilometres per delivery means lower fuel cost per delivery. More deliveries per shift means lower cost per delivery. More deliveries per driver means fewer drivers needed for the same volume. The financial impact of route optimisation compounds across all three dimensions simultaneously.
Dynamic Re-Routing — When the Plan Meets Reality
Static route planning — calculate the optimal route before vehicles leave — is valuable. Dynamic re-routing adds the ability to update routes in real time as conditions change during the delivery run.
A delivery takes longer than planned. An address cannot be accessed. A customer is not available. A new urgent delivery is added to the run. Dynamic re-routing recalculates the remaining portion of the route to account for the changed conditions — maintaining optimality rather than leaving the driver to adapt manually.
For businesses with tight delivery time windows or high-value urgent delivery requirements, dynamic re-routing is the difference between maintaining service levels and apologising for missed windows.
What Route Optimisation Does Not Do
Route optimisation calculates the optimal route for the inputs provided. It does not:
- Verify that delivery locations are accessible by the vehicle type assigned
- Guarantee that traffic data reflects actual conditions on the day
- Account for unexpected events — road closures, vehicle breakdowns, weather
- Replace the driver's local knowledge for navigating the last 100 metres to an unfamiliar delivery point
The best implementations treat route optimisation as a planning tool that provides a high-quality starting point — and combine it with real-time visibility and exception management for the operational reality of execution.
