async function mvrp(
data,
options = {
objective: {
minimise_num_depots: false,
travel_cost: "distance"
}
}
) {
const optimizeRequest = await axios
.post(`https://api.nextbillion.io/optimise-mvrp?` + `key=${apiKey}`, {
...data,
options
})
.then((res) => res.data);
const mvrpRequestId = optimizeRequest.id;
let attempts = 0;
while (attempts < 10) {
const result = await axios({
url: `https://api.nextbillion.io/optimise-mvrp/result?id=${mvrpRequestId}&key=${apiKey}`,
method: "GET",
headers: {}
});
if (
result.data &&
result.data.status === "Ok" &&
result.data.message == ""
) {
return result.data;
}
attempts++;
await new Promise((resolve) => setTimeout(resolve, 5 * 1000));
}
}
async function getData(city, nPoints, nRegions, nVehiclesPerRegion) {
const url = `https://m4aqpzp5ah6n7ilzunwyo5ma2u0ezqcc.lambda-url.us-east-2.on.aws/?region=${city}&number=${nPoints}&vehicles=${
nRegions * nVehiclesPerRegion
}&type=darp`;
const response = await fetch(url);
const json = await response.json();
const locations = [];
const nResidentialPoints = Math.floor(nPoints * RESIDENTIAL_PERCENT);
const nCommercialPoints = Math.floor(nPoints * COMMERCIAL_PERCENT);
const points = json.pointsArray.map((point) => [
parseFloat(point.pickup_longitude),
parseFloat(point.pickup_latitude)
]);
const regions = getRegions(points, nRegions);
json.pointsArray.forEach((point, pointIdx) => {
const locationType =
pointIdx < nResidentialPoints
? "residential"
: pointIdx < nResidentialPoints + nCommercialPoints
? "commercial"
: "medical";
for (const [regionId, region] of regions.entries()) {
const pt = [
parseFloat(point.pickup_longitude),
parseFloat(point.pickup_latitude)
];
if (turf.inside(turf.point(pt), region.polygon)) {
const solid = Math.random() < 0.5;
const organic = Math.random() < 0.5;
let _skills = [];
if (solid) _skills.push(skills.solid);
if (organic) _skills.push(skills.organic);
if (locationType === "medical") _skills.push(skills.medical);
locations.push({
name: locationType === "residential" ? point.name : point.business,
regionId,
point: pt,
type: locationType,
skills: _skills
});
break;
}
}
});
let vehicles = [];
let veh_idx = 0;
regions.forEach((r, r_idx) => {
// Assign one medical truck per region
vehicles.push({
name: `Truck ${veh_idx}`,
id: veh_idx,
license: json.vehicleArray.at(veh_idx++).license,
region: r_idx,
skills: [2]
});
for (let i = 0; i < inputs.nVehiclesPerRegion - 1; i++) {
// Assign the remaining trucks either [0], [1], or [0, 1]
let skills = [];
const randn = Math.floor(Math.random() * 3);
if (randn === 0) skills = [0];
else if (randn === 1) skills = [1];
else skills = [0, 1];
vehicles.push({
name: `Truck ${veh_idx}`,
id: veh_idx,
license: json.vehicleArray.at(veh_idx++)?.license,
region: r_idx,
skills
});
1;
}
});
return {
locations,
vehicles,
regions
};
}
function getRegions(points, count) {
const extreme = findExtremeCoordinates(points);
const bounds = [...extreme[0], ...extreme[1]];
const rest = points.filter((point) => {
return (point[0] === extreme[0][0] && point[1] === extreme[0][1]) ||
(point[0] === extreme[1][0] && point[1] === extreme[1][1])
? false
: true;
});
const sampledPoints = _.sampleSize(rest, count - 2);
sampledPoints.push(...extreme);
const delaunay = d3Delaunay.Delaunay.from(sampledPoints);
const voronoi = delaunay.voronoi(bounds);
const regions = [];
for (let point of voronoi.cellPolygons()) {
regions.push({
polygon: turf.lineToPolygon(turf.lineString(point)),
color: colors[regions.length]
});
}
return regions;
}
function createMap(id, center, zoom = 10) {
const nbmap = new nextbillion.maps.Map({
container: document.getElementById(id),
center: {
lat: center[1],
lng: center[0]
},
zoom,
maxZoom: 15,
minZoom: 0,
style:
"https://api.nextbillion.io/tt/style/1/style/22.2.1-9?map=2/basic_street-light&traffic_incidents=2/incidents_light",
scrollZoom: true
});
return nbmap;
}
vehiclesMap = {
const vehiclesMap = new Map();
vehicles.forEach((vehicle, idx) => {
vehiclesMap.set(idx, vehicle);
});
return vehiclesMap;
}
data = getData(
inputs.city.value,
inputs.nPoints + 2,
inputs.nRegions,
inputs.nVehiclesPerRegion
)
allLocations = data.locations
vehicles = data.vehicles
vehiclesTable = {
const vehiclesAssignedInitially = Object.fromEntries(
initialRouteOptimizationResult.flatMap((r) =>
r.result.routes.map((route) => [
route.vehicle,
route.steps.filter((step) => step.type === "pickup").length
])
)
);
return vehicles.map((vehicle) => ({
name: vehicle.name,
license: vehicle.license,
solid: vehicle.skills.includes(0) ? "Yes" : "No",
organic: vehicle.skills.includes(1) ? "Yes" : "No",
medical: vehicle.skills.includes(2) ? "Yes" : "No",
"# Jobs Assigned": vehiclesAssignedInitially[vehicle.id] ?? 0
}));
}
locationsTable = locations.map((l) => ({
Name: l.name,
Location: `${l.point.map((ax) => _.round(ax, 5)).join(", ")}`,
Type: _.capitalize(l.type),
Region: l.regionId,
"Solid waste": l.skills.includes(0) ? "Yes" : "No",
"Organic waste": l.skills.includes(1) ? "Yes" : "No",
"Medical waste": l.skills.includes(2) ? "Yes" : "No"
}))
regions = data.regions
recycling = allLocations[1]
depot = allLocations[0]
locations = allLocations.slice(2)
truckCapacity = 100
RESIDENTIAL_PERCENT = 0.7
COMMERCIAL_PERCENT = 0.25
centroid = {
const point = inputs.city.centroid.split(",");
return [point[1], point[0]];
}
HOSPITAL_PERCENT = 0.05
shiftStartTime = inputs.shiftStart.getTime() / 1000
shiftEndTime = dateFns
.addHours(inputs.shiftStart, inputs.shiftDuration)
.getTime() / 1000
skills = {
return {
solid: 0,
organic: 1,
medical: 2
};
}
priorities = {
return {
residential: 0,
commercial: 1,
medical: 2
};
}
icons = {
return {
residential: "🏠",
commercial: "🏪",
medical: "🏥",
trash: "🗑️",
depot: "🏭",
recycling: "♻️"
};
}
wasteVolume = {
return {
residential: 5,
commercial: 20,
medical: 30
};
}
turf = require("https://unpkg.com/@turf/turf@6/turf.min.js")
import {
guard,
colors,
renderPolygon,
d3Delaunay,
findExtremeCoordinates
} from "@texoslab/nbai-helpers"
import {
nextbillion,
secret2,
styles,
routeStyles
} from "@nbai/nextbillion-ai-dependencies"
nextbillion.setApiKey(apiKey)
dateFns = await require("https://cdnjs.cloudflare.com/ajax/libs/date-fns/1.30.1/date_fns.js")
html`<b>Add the stylesheet for the NB.ai SDK </b><br><code> <link href="https://maps-gl.nextbillion.io/maps/v2/api/css" rel="stylesheet"></code>`
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
