Javascript
This is example how to call solver methods from javascript in browser. You need to build vrp-cli library for
WebAssembly target. To do this, you can use wasm-pack:
cd vrp-cli
wasm-pack build --target web
It should generate wasm build + some javascript files for you. If you want to have a smaller binary, you can try
to build without default features: csv-format, hre-format, scientific-format.
To test it, use the following index.html file:
<html>
<head>
<meta content="text/html;charset=utf-8" http-equiv="Content-Type"/>
</head>
<body>
<script type="module">
import init, { get_routing_locations, solve_pragmatic } from './pkg/vrp_cli.js';
async function run() {
await init();
const pragmatic_problem = JSON.parse(`
{
"plan": {
"jobs": [
{
"id": "job1",
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.52599,
"lng": 13.45413
},
"duration": 300.0,
"times": [
[
"2019-07-04T09:00:00Z",
"2019-07-04T18:00:00Z"
],
[
"2019-07-05T09:00:00Z",
"2019-07-05T18:00:00Z"
]
]
}
],
"demand": [
1
]
}
]
},
{
"id": "job2",
"pickups": [
{
"places": [
{
"location": {
"lat": 52.5225,
"lng": 13.4095
},
"duration": 240.0,
"times": [
[
"2019-07-04T10:00:00Z",
"2019-07-04T16:00:00Z"
]
]
}
],
"demand": [
1
]
}
]
},
{
"id": "job3",
"pickups": [
{
"places": [
{
"location": {
"lat": 52.5225,
"lng": 13.4095
},
"duration": 300.0
}
],
"demand": [
1
],
"tag": "p1"
}
],
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.5165,
"lng": 13.3808
},
"duration": 300.0
}
],
"demand": [
1
],
"tag": "d1"
}
]
}
]
},
"fleet": {
"vehicles": [
{
"typeId": "vehicle",
"vehicleIds": [
"vehicle_1"
],
"profile": {
"matrix": "normal_car"
},
"costs": {
"fixed": 22.0,
"distance": 0.0002,
"time": 0.004806
},
"shifts": [
{
"start": {
"earliest": "2019-07-04T09:00:00Z",
"location": {
"lat": 52.5316,
"lng": 13.3884
}
},
"end": {
"latest": "2019-07-04T18:00:00Z",
"location": {
"lat": 52.5316,
"lng": 13.3884
}
}
}
],
"capacity": [
10
]
}
],
"profiles": [
{
"name": "normal_car"
}
]
}
}
`);
const locations = get_routing_locations(pragmatic_problem);
console.log(`routing locations are:\n ${locations}`);
// NOTE let's assume we got routing matrix data for locations somehow
// NOTE or just pass an empty array to use great-circle distance approximation
const matrix_data= [
{
"matrix": "normal_car",
"travelTimes": [
0, 609, 981, 906,
813, 0, 371, 590,
1055, 514, 0, 439,
948, 511, 463, 0
],
"distances": [
0, 3840, 5994, 5333,
4696, 0, 2154, 3226,
5763, 2674, 0, 2145,
5112, 2470, 2152, 0
]
}
];
// config provides the way to tweak algorithm behavior
const config = {
"termination": {
"maxTime": 10,
"maxGenerations": 1000
}
};
const solution = solve_pragmatic(pragmatic_problem, matrix_data, config);
console.log(`solution is:\n ${solution}`);
}
run();
</script>
</body>
</html>