{
  "resources": [
    {
      "name": "courier-1",
      "shifts": [
        {
          "from": "2024-03-15T08:00:00Z",
          "to": "2024-03-15T18:00:00Z",
          "start": {
            "name": "Depot",
            "latitude": 52.5200,
            "longitude": 13.4050
          },
          "end": {
            "name": "Depot",
            "latitude": 52.5200,
            "longitude": 13.4050
          }
        }
      ],
      "capacity": [50]
    }
  ],
  "jobs": [
    {
      "name": "delivery-1",
      "location": {
        "name": "Customer A - Alexanderplatz",
        "latitude": 52.5219,
        "longitude": 13.4132
      },
      "duration": 300,
      "load": [5]
    },
    {
      "name": "delivery-2",
      "location": {
        "name": "Customer B - Potsdamer Platz",
        "latitude": 52.5096,
        "longitude": 13.3761
      },
      "duration": 300,
      "load": [8]
    },
    {
      "name": "delivery-3",
      "location": {
        "name": "Customer C - Brandenburger Tor",
        "latitude": 52.5163,
        "longitude": 13.3777
      },
      "duration": 300,
      "load": [6]
    },
    {
      "name": "delivery-4",
      "location": {
        "name": "Customer D - Checkpoint Charlie",
        "latitude": 52.5075,
        "longitude": 13.3903
      },
      "duration": 300,
      "load": [4]
    },
    {
      "name": "delivery-5",
      "location": {
        "name": "Customer E - Berlin Cathedral",
        "latitude": 52.5191,
        "longitude": 13.4011
      },
      "duration": 300,
      "load": [7]
    }
  ],
  "options": {
    "routingEngine": "OSM",
    "euclidian": false,
    "traffic": 1.0
  }
}

{
  "id": "vrp_job_123456",
  "status": "SOLVED",
  "solution": {
    "routes": [
      {
        "resource": "courier-1",
        "jobs": [
          {
            "job": "delivery-5",
            "arrival": "2024-03-15T08:12:00Z",
            "departure": "2024-03-15T08:17:00Z",
            "travelTime": 720,
            "distance": 2847
          },
          {
            "job": "delivery-1",
            "arrival": "2024-03-15T08:21:00Z",
            "departure": "2024-03-15T08:26:00Z",
            "travelTime": 240,
            "distance": 1123
          },
          {
            "job": "delivery-4",
            "arrival": "2024-03-15T08:34:00Z",
            "departure": "2024-03-15T08:39:00Z",
            "travelTime": 480,
            "distance": 2256
          },
          {
            "job": "delivery-2",
            "arrival": "2024-03-15T08:47:00Z",
            "departure": "2024-03-15T08:52:00Z",
            "travelTime": 480,
            "distance": 2103
          },
          {
            "job": "delivery-3",
            "arrival": "2024-03-15T08:54:00Z",
            "departure": "2024-03-15T08:59:00Z",
            "travelTime": 120,
            "distance": 534
          }
        ],
        "summary": {
          "totalTravelTime": 3240,
          "totalDistance": 12684,
          "totalDuration": 5340,
          "totalJobs": 5,
          "departureTime": "2024-03-15T08:00:00Z",
          "arrivalTime": "2024-03-15T09:18:00Z"
        }
      }
    ],
    "unassigned": [],
    "metrics": {
      "totalTravelTime": 3240,
      "totalDistance": 12684,
      "totalJobs": 5,
      "assignedJobs": 5,
      "unassignedJobs": 0
    }
  }
}

​
Basic Routing

This example demonstrates how to solve a simple vehicle routing problem with real road distances using OpenStreetMap (OSM) data. We’ll route a single vehicle to visit 5 delivery locations in Berlin, Germany.

​
Business Scenario

A local courier company needs to deliver packages to 5 customers in Berlin. They want to:
  • Find the most efficient route visiting all customers
  • Use actual road distances, not straight-line distances
  • Start and end at their depot
  • Complete all deliveries in one trip

​
Complete Request

{
  "resources": [
    {
      "name": "courier-1",
      "shifts": [
        {
          "from": "2024-03-15T08:00:00Z",
          "to": "2024-03-15T18:00:00Z",
          "start": {
            "name": "Depot",
            "latitude": 52.5200,
            "longitude": 13.4050
          },
          "end": {
            "name": "Depot",
            "latitude": 52.5200,
            "longitude": 13.4050
          }
        }
      ],
      "capacity": [50]
    }
  ],
  "jobs": [
    {
      "name": "delivery-1",
      "location": {
        "name": "Customer A - Alexanderplatz",
        "latitude": 52.5219,
        "longitude": 13.4132
      },
      "duration": 300,
      "load": [5]
    },
    {
      "name": "delivery-2",
      "location": {
        "name": "Customer B - Potsdamer Platz",
        "latitude": 52.5096,
        "longitude": 13.3761
      },
      "duration": 300,
      "load": [8]
    },
    {
      "name": "delivery-3",
      "location": {
        "name": "Customer C - Brandenburger Tor",
        "latitude": 52.5163,
        "longitude": 13.3777
      },
      "duration": 300,
      "load": [6]
    },
    {
      "name": "delivery-4",
      "location": {
        "name": "Customer D - Checkpoint Charlie",
        "latitude": 52.5075,
        "longitude": 13.3903
      },
      "duration": 300,
      "load": [4]
    },
    {
      "name": "delivery-5",
      "location": {
        "name": "Customer E - Berlin Cathedral",
        "latitude": 52.5191,
        "longitude": 13.4011
      },
      "duration": 300,
      "load": [7]
    }
  ],
  "options": {
    "routingEngine": "OSM",
    "euclidian": false,
    "traffic": 1.0
  }
}

​
Key Configuration Choices

​
Routing Engine

"options": {
  "routingEngine": "OSM",
  "euclidian": false
}
Distance Calculation Methods:
  • "routingEngine": "OSM" - Uses OpenStreetMap for real road distances
  • "euclidian": true - Would use straight-line distances (faster but less accurate)
  • Other engines: "TOMTOM", "GOOGLE", "ANYMAP"

​
Location Details

Each location includes:
  • Name: Human-readable identifier for clarity
  • Coordinates: Latitude/longitude for geocoding
  • Duration: Service time at each stop (5 minutes)
  • Load: Package size/weight

​
Vehicle Configuration

  • Shift: 10-hour working day (8 AM - 6 PM)
  • Start/End: Same depot location (round trip)
  • Capacity: 50 units (sum of all loads = 30 units)

​
Expected Response

{
  "id": "vrp_job_123456",
  "status": "SOLVED",
  "solution": {
    "routes": [
      {
        "resource": "courier-1",
        "jobs": [
          {
            "job": "delivery-5",
            "arrival": "2024-03-15T08:12:00Z",
            "departure": "2024-03-15T08:17:00Z",
            "travelTime": 720,
            "distance": 2847
          },
          {
            "job": "delivery-1",
            "arrival": "2024-03-15T08:21:00Z",
            "departure": "2024-03-15T08:26:00Z",
            "travelTime": 240,
            "distance": 1123
          },
          {
            "job": "delivery-4",
            "arrival": "2024-03-15T08:34:00Z",
            "departure": "2024-03-15T08:39:00Z",
            "travelTime": 480,
            "distance": 2256
          },
          {
            "job": "delivery-2",
            "arrival": "2024-03-15T08:47:00Z",
            "departure": "2024-03-15T08:52:00Z",
            "travelTime": 480,
            "distance": 2103
          },
          {
            "job": "delivery-3",
            "arrival": "2024-03-15T08:54:00Z",
            "departure": "2024-03-15T08:59:00Z",
            "travelTime": 120,
            "distance": 534
          }
        ],
        "summary": {
          "totalTravelTime": 3240,
          "totalDistance": 12684,
          "totalDuration": 5340,
          "totalJobs": 5,
          "departureTime": "2024-03-15T08:00:00Z",
          "arrivalTime": "2024-03-15T09:18:00Z"
        }
      }
    ],
    "unassigned": [],
    "metrics": {
      "totalTravelTime": 3240,
      "totalDistance": 12684,
      "totalJobs": 5,
      "assignedJobs": 5,
      "unassignedJobs": 0
    }
  }
}

​
Understanding the Results

​
Route Sequence

The optimized route visits customers in this order:
  1. Depot → Customer E (Berlin Cathedral)
  2. → Customer A (Alexanderplatz)
  3. → Customer D (Checkpoint Charlie)
  4. → Customer B (Potsdamer Platz)
  5. → Customer C (Brandenburger Tor)
  6. → Depot

​
Distance Comparison

To see the difference real distances make, compare with Euclidean distances: 
{
  "options": {
    "routingEngine": "OSM",
    "euclidian": false
  }
}
// Total distance: ~12.7 km
// Accounts for: one-way streets, roads, traffic rules
Real road distances are typically 20-50% longer than straight-line distances in urban areas due to the road network structure.

​
Try It Yourself

1

Get API Access

Obtain your API key from the Solvice Dashboard
2

Send Request

curl -X POST 'https://api.solvice.io/v2/vrp/solve' \
  -H 'Authorization: YOUR_API_KEY' \
  -H 'Content-Type: application/json' \
  -d '{
    "resources": [{
      "name": "courier-1",
      "shifts": [{
        "from": "2024-03-15T08:00:00Z",
        "to": "2024-03-15T18:00:00Z",
        "start": {"latitude": 52.5200, "longitude": 13.4050},
        "end": {"latitude": 52.5200, "longitude": 13.4050}
      }],
      "capacity": [50]
    }],
    "jobs": [
      {"name": "delivery-1", "location": {"latitude": 52.5219, "longitude": 13.4132}, "duration": 300, "load": [5]},
      {"name": "delivery-2", "location": {"latitude": 52.5096, "longitude": 13.3761}, "duration": 300, "load": [8]},
      {"name": "delivery-3", "location": {"latitude": 52.5163, "longitude": 13.3777}, "duration": 300, "load": [6]},
      {"name": "delivery-4", "location": {"latitude": 52.5075, "longitude": 13.3903}, "duration": 300, "load": [4]},
      {"name": "delivery-5", "location": {"latitude": 52.5191, "longitude": 13.4011}, "duration": 300, "load": [7]}
    ],
    "options": {"routingEngine": "OSM"}
  }'
3

Check Status

curl -X GET 'https://api.solvice.io/v2/vrp/jobs/{job_id}/status' \
  -H 'Authorization: YOUR_API_KEY'
4

Get Solution

curl -X GET 'https://api.solvice.io/v2/vrp/jobs/{job_id}/solution' \
  -H 'Authorization: YOUR_API_KEY'

​
Next Steps

Now that you understand basic routing with real distances:

Add Time Windows

Learn how to handle customer availability constraints

Multiple Vehicles

Scale up to fleet routing with multiple vehicles

Capacity Planning

Understand advanced capacity constraints

Distance Matrix

Optimize with pre-calculated distances