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How to optimize the route

Basic Order Optimization​

GraphQL query

You can optimize the route to reduce costs, distance, and the time taken and more.

const fetch = require("node-fetch")

fetch("https://backend.impargo.eu/", {
  method: "POST",
  headers: {
    "authorization": token,
    "content-type": "application/json",
  },
  body: JSON.stringify([{
    "operationName": "Optimize",
    "variables": {
      "stops": [
        {"lat": 43.34991, "lon": 1.86602},
        {"lat": 53.52996, "lon": -8.77419},
        {"lat": 48.13641, "lon": 11.57754}
      ],
      "fixLastStop": false,
      "departureDate": null
    },
    "query": `query Optimize($stops: [OptimizationStop]!, $fixLastStop: Boolean, $departureDate: DateTime) {
      optimize(
        stops: $stops
        fixLastStop: $fixLastStop
        departureDate: $departureDate
      ) {
        order
        warning
        __typename
      }
    }`
  }])
})
.then(response => response.json())
.then(data => {
  const graphqlData = data[0].data.optimize;
  console.log("GraphQL Response:", graphqlData);
})
.catch(error => {
  console.error("Fetch Error:", error);
});

[
    {
        "data": {
            "optimize": {
                "order": [
                    0,
                    1,
                    2
                ],
                "warning": null,
                "__typename": "OptimizationResult"
            }
        }
    }
]

Advanced Time Planning Optimization​

This example demonstrates how to optimize a route considering time windows for each stop, waiting time at stops, and a specific departure date and time.

const fetch = require("node-fetch")

fetch("https://backend.impargo.eu/", {
  method: "POST",
  headers: {
    "authorization": token,
    "content-type": "application/json",
  },
  body: JSON.stringify([{
    "operationName": "Optimize",
    "variables": {
      "stops": [
        {
          "lat": 52.53131,
          "lon": 13.3503,
          "timeWindows": [
            { "from": "09:00", "to": "14:00" }
          ],
          "waitingTime": 1800
        },
        {
          "lat": 52.40326,
          "lon": 13.06908,
          "timeWindows": [
            { "from": "08:00", "to": "16:00" }
          ],
          "waitingTime": 900
        },
        {
          "lat": 52.51661,
          "lon": 13.37706,
          "timeWindows": [
            { "from": "08:00", "to": "16:00" }
          ],
          "waitingTime": 1800
        }
      ],
      "fixLastStop": false,
      "departureDate": "2025-10-18T08:00:00.000Z"
    },
    "query": `query Optimize(
  $stops: [OptimizationStop]!
  $fixLastStop: Boolean
  $departureDate: DateTime
) {
  optimize(
    stops: $stops
    fixLastStop: $fixLastStop
    departureDate: $departureDate
  ) {
    order
    warning
  }
}`
  }])
})
.then(response => response.json())
.then(data => {
  const graphqlData = data[0].data.optimize;
  console.log("GraphQL Response:", graphqlData);
})
.catch(error => {
  console.error("Fetch Error:", error);
});

[
    {
        "data": {
            "optimize": {
                "order": [0, 2, 1],
                "warning": null
            }
        }
    }
]

In this example, each stop has a time window and waiting time. The optimization considers these constraints and the specified departure date/time to calculate the best order of stops.