New Feature: Balance Workloads Across Your Drivers

Suppose you have a fleet of 5 drivers and 50 delivery stops. You want each driver to have a fair share of work — not one driver working 10 hours while another finishes in 2.

Until now, you could use min-max to minimize the longest route. But min-max only cares about the maximum — it doesn’t even ensure all available drivers are employed, let alone that they have similar workloads.

The new balance objective solves this by optimizing for equal distribution of work across all drivers.

How It Works

Instead of minimizing the maximum value, balance minimizes the coefficient of variation (CV) — the ratio of standard deviation to mean — of workloads. This means it actively tries to make all routes similar in length, while still maintaining compact routes where possible.

"objectives": [
  {
    "type": "balance",
    "value": "completion_time",
    "level": 2
  }
]

Two Balancing Modes

Balance working time (completion_time): Each driver spends roughly the same total time — including driving, service, and waiting.

Balance number of stops (activities): Each driver visits roughly the same number of customers — useful when stops have similar durations.

The Level Parameter

The level controls how strongly to prioritize fairness over travel efficiency:

Level	Behavior
1	Mild balance — accepts some variation for shorter routes
2	Moderate balance (default)
3	Strict balance — prioritizes equal workloads

Example

Let me illustrate balancing working time with a concrete example. Consider 50 delivery stops across Munich with 5 available drivers: 10 corporate events (20 min service each) and 40 quick office deliveries (5 min each). (view example request)

Objective	Drivers	Total Distance	Working Time Range	Spread
min completion_time	1	141 km	12h 38min	—
balance completion_time L1	5	173 km	2h 25min – 3h 04min	39 min
balance completion_time L3	5	190 km	2h 45min – 2h 59min	14 min

The default min objective uses only 1 driver — it optimizes total time, not fairness.

With balance at level 1, all 5 drivers are employed with working times within 39 minutes of each other. Level 3 tightens this to just 14 minutes, at the cost of 10% more total travel.

The map below shows how the 5 routes fan out across Munich, each driver covering a distinct area:

Handling Outlier Service Times

What if one stop takes 2 hours instead of 5 minutes? The algorithm compensates by assigning fewer stops to that driver: (view example request)

Driver	Stops	Working Time
driver-5	4	3h 16min
driver-2	12	3h 07min
driver-3	10	3h 12min
driver-4	12	3h 14min
driver-1	12	3h 19min

Driver-5 handles the 2-hour stop and gets only 4 stops total, while others get 10–12. Yet working times stay within 12 minutes of each other.

In the map below, driver-5’s purple route is the shortest — the 2-hour stop is the most western location on the map. The other drivers pick up the remaining stops:

Performance

Calculation is fairly fast for small and medium-sized problems (up to 300 stops). The 50-stop example above completed in about 1 second. With 150 stops and 20 drivers, calculation takes about 5 seconds.

Current Limitations

This feature is in beta and currently supports services only. Requests that combine balance objectives with shipments will return a 400 error.

Try it in the API Explorer and let us know your feedback! Full documentation is available at docs.graphhopper.com.