What is route optimisation?
Route optimisation finds the most efficient order to visit a set of stops — minimising total travel time or distance across multiple destinations. It's distinct from simple navigation (getting from A to B) because it solves the ordering problem: given 15 deliveries, which sequence minimises total drive time?
This is the core technology behind courier apps, field service dispatch, and delivery management platforms. At its heart it's a variant of the Travelling Salesman Problem — an NP-hard computational challenge that real-world systems solve using heuristic algorithms rather than exhaustive search.
Real deployments add constraints that make the problem harder: time windows (the customer is only available 9–11am), vehicle capacity (the van can only carry so much), driver start and end locations (routes begin at a depot), and skill matching (only certain technicians can do certain jobs). Each constraint adds complexity.
When does your app need it?
- You're dispatching drivers, technicians, or couriers to multiple stops per day
- Manually sequencing deliveries or service calls is costing time and fuel
- Customers have requested delivery or service windows that must be respected
- You're managing a fleet with different vehicle capacities or driver skill sets
- You want to reduce fuel costs and environmental impact through more efficient routing
- You're competing with logistics platforms and need comparable routing intelligence
How much does it cost?
Adding route optimisation typically adds 13–27 hours of development — roughly $2,000–$6,000 AUD.
The simpler end covers basic stop-ordering for a single vehicle using the Google Routes API, with results displayed on a map. The higher end involves multi-vehicle routing, time windows, capacity constraints, a dispatch interface, driver mobile app integration, and route re-optimisation mid-day when stops are added or cancelled.
Ongoing API costs for large route sets can be meaningful — Google's Routes API (Compute Routes) charges per request. For high-volume operations, purpose-built routing APIs from HERE or Routific may be more cost-effective.
How it's typically built
For basic routing, the Google Routes API accepts a list of waypoints and returns an optimised order. For more complex multi-vehicle problems with constraints, dedicated Vehicle Routing Problem (VRP) APIs like Routific, OptimoRoute, or OR-Tools (Google's open-source operations research library) are better suited.
The typical architecture: stop data is submitted to the routing API → optimised routes are returned per vehicle → routes are displayed on a map for the dispatcher → drivers receive their route on a mobile app. Re-optimisation (adding a stop mid-route) calls the API again with the remaining stops.
Australian context: Australian road data quality is generally good in major cities; rural routing can be less reliable. If your routes include regional or outback areas, test thoroughly — some routing APIs have gaps in minor road data outside capital cities.
Questions to ask your developer
- Which routing API are you using and does it support our constraint types? Time windows and multi-vehicle routing need a capable API, not just Google Maps Directions.
- How many vehicles and stops does this need to handle? Routing complexity and API cost scale with problem size — get a clear scope.
- What happens when a stop is added or cancelled mid-day? Re-optimisation should be a first-class feature, not an afterthought.
- Is there a dispatcher view and a driver view? These are typically separate interfaces with different requirements.
- What are the ongoing routing API costs at our expected volume? For daily route runs across a fleet, this becomes an operational cost worth budgeting.
See also: GPS tracking · Maps and geolocation · Geofencing · App cost calculator