2b:null 2c:["$","title",null,{"children":"Waste Collection Route Optimization (main) | Shweta Singh's Workspace | Observable"}] 31:T6d5,md` # Approach * We use a technique called Voronoi tessellation, which involves dividing space into regions based on proximity to points or objects. In our case, we employ Voronoi tessellation to generate a set of random, non-intersecting polygons that represent distinct regions. * We randomly generate locations that fall within one of these regions and assign them one or more waste types: solid, organic, and medical. Each location represents either a residential property, a commercial property, or a hospital. Different priority levels are assigned based on the type: residential properties have a priority of 0, commercial properties have a priority of 1, and hospitals have a priority of 2. * All trucks have a capacity of ${truckCapacity} cubic meters. A residential bin has a capacity of ${wasteVolume.residential} cubic meters, commercial bins have a capacity of ${wasteVolume.commercial}, and hospitals have a capacity of ${wasteVolume.medical}. * We allocate **${inputs.nVehiclesPerRegion} trucks per region**, with one designated for handling medical waste and the remaining trucks capable of handling solid waste, organic waste, or both. * The job of a truck driver is to collect waste from the assigned bins and transport it to the recycling center once all the collection is complete. Once the waste is disposed of at the recycling center, the driver is responsible for returning the truck to the depot. * We utilize the Route Optimization API for each region to find optimal paths for the trucks assigned to service their respective locations. * If there are any waste bins left unassigned in the previous step, we run the Route Optimization API again using the unassigned trucks, but this time, we do it for all regions at once. `32:T58b,viewof inputs = { let shiftStart = new Date(); shiftStart.setDate(new Date().getDate() + 1); shiftStart.setHours(5); shiftStart.setMinutes(45); shiftStart.setSeconds(0); shiftStart.setMilliseconds(0); shiftStart.toLocaleDateString(); return guard(({ template, ...rest }) => { return Inputs.form( { // city: Inputs.select(cities, { // label: "Select city", // format: (x) => x.name, // value: cities.find((t) => t.name === "Columbus") // }), nRegions: Inputs.select( [5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20], { label: "Number of zones", value: 8 } ), nPoints: Inputs.select([50, 100, 200, 250, 300, 400, 500, 1000], { label: "Number of waste bins", value: 200 }), nVehiclesPerRegion: Inputs.select([5, 10, 15, 20, 50, 100], { label: "Number of vehicles (per region)", value: 5 }), shiftDuration: Inputs.select( Array.from(Array(20).keys()).map((k) => k * 0.5 + 0.5), { label: "Shift duration (in hours)", value: 5 } ), shiftStart: Inputs.datetime({ value: shiftStart.toISOString().slice(0, -1), label: "Shift start time" }) }, { template } ); }); }33:T534,{ // Map 1 apiKey; const nbmap = createMap("map", centroid, 10); nbmap.on("load", () => { regions.forEach((region) => { renderPolygon(nbmap.map, region.polygon, region.color, 0.4); }); { const el = document.createElement("div"); el.innerText = icons.depot; el.style.fontSize = "40px"; new nextbillion.maps.Marker({ element: el }) .setLngLat({ lat: depot.point[1], lng: depot.point[0] }) .addTo(nbmap.map); } { const el = document.createElement("div"); el.innerText = icons.recycling; el.style.fontSize = "36px"; new nextbillion.maps.Marker({ element: el }) .setLngLat({ lat: recycling.point[1], lng: recycling.point[0] }) .addTo(nbmap.map); } locations.forEach((location) => { if (!showBins.includes(location.type)) return; const el = document.createElement("div"); el.innerText = icons[location.type]; if (location.type === "residential") el.style.fontSize = "9px"; if (location.type === "commercial") el.style.fontSize = "12px"; if (location.type === "medical") el.style.fontSize = "20px"; const marker = new nextbillion.maps.Marker({ element: el }) .setLngLat({ lat: location.point[1], lng: location.point[0] }) .addTo(nbmap.map); }); }); }34:T48e,selectedRegionsTable = { const result = focusedRegion.result.result; let regionBinIds = []; for (const [locIdx, loc] of locations.entries()) { if (loc.regionId === focusedRegion.regionId) { regionBinIds.push(locIdx); } } const unassignedBinIds = result.unassigned?.filter((_, idx) => idx % 2 === 0)?.map((x) => x.id) ?? []; const assignedBinIds = _.difference(regionBinIds, unassignedBinIds); const assignedBins = assignedBinIds.map((id) => locationsMap.get(id)); const unassignedBins = unassignedBinIds.map((id) => { // location id 0, 1 are depot and recycling bin respectively return locationsMap.get(id + 2); }); return [ [ "Unserviceable bins", unassignedBins.filter((b) => b?.type === "residential").length, unassignedBins.filter((b) => b?.type === "commercial").length, unassignedBins.filter((b) => b?.type === "medical").length ], [ "Serviceable Bins", assignedBins.filter((b) => b?.type === "residential").length, assignedBins.filter((b) => b?.type === "commercial").length, assignedBins.filter((b) => b?.type === "medical").length ] ]; }35:T82a,{ // Map 2 const nbmap = createMap("result-map", centroid, 10); nbmap.on("load", () => { { const el = document.createElement("div"); el.innerText = icons.depot; el.style.fontSize = "40px"; new nextbillion.maps.Marker({ element: el }) .setLngLat({ lat: depot.point[1], lng: depot.point[0] }) .addTo(nbmap.map); } { const el = document.createElement("div"); el.innerText = icons.recycling; el.style.fontSize = "36px"; new nextbillion.maps.Marker({ element: el }) .setLngLat({ lat: recycling.point[1], lng: recycling.point[0] }) .addTo(nbmap.map); } const region = regions.at(focusedRegion.regionId); locations.forEach((location) => { if (location.regionId !== focusedRegion.regionId) return; const el = document.createElement("div"); el.innerText = icons[location.type]; if (location.type === "residential") el.style.fontSize = "9px"; if (location.type === "commercial") el.style.fontSize = "12px"; if (location.type === "medical") el.style.fontSize = "20px"; const marker = new nextbillion.maps.Marker({ element: el }) .setLngLat({ lat: location.point[1], lng: location.point[0] }) .addTo(nbmap.map); }); renderPolygon(nbmap.map, region.polygon, region.color, 0.4); focusedRegion.result.result.routes.forEach((route, idx) => { if (selectedVehicles.indexOf(route.vehicle) === -1) return; nbmap.map.addSource(`route-${idx}`, { type: "geojson", data: { type: "Feature", properties: {}, geometry: { type: "LineString", coordinates: nextbillion.utils.polyline .decode(route.geometry) .map((c) => c.reverse()) } } }); nbmap.map.addLayer({ id: `route-${idx}`, type: "line", source: `route-${idx}`, layout: { "line-join": "round", "line-cap": "round" }, paint: { "line-color": colors[idx], "line-width": 4 } }); }); }); }36:T8cf,{ // Map 3 if (unassignedBins.length === 0) return; const container = html`

`; yield container; const nbmap = createMap("reassignment-map", centroid, 10); nbmap.on("load", () => { { const el = document.createElement("div"); el.innerText = icons.depot; el.style.fontSize = "40px"; new nextbillion.maps.Marker({ element: el }) .setLngLat({ lat: depot.point[1], lng: depot.point[0] }) .addTo(nbmap.map); } { const el = document.createElement("div"); el.innerText = icons.recycling; el.style.fontSize = "36px"; new nextbillion.maps.Marker({ element: el }) .setLngLat({ lat: recycling.point[1], lng: recycling.point[0] }) .addTo(nbmap.map); } const region = regions.at(focusedRegion.regionId); regions.forEach((region) => { renderPolygon(nbmap.map, region.polygon, region.color, 0.4); }); unassignedBins.forEach((location) => { const el = document.createElement("div"); el.innerText = icons[location.type]; if (location.type === "residential") el.style.fontSize = "9px"; if (location.type === "commercial") el.style.fontSize = "12px"; if (location.type === "medical") el.style.fontSize = "20px"; const marker = new nextbillion.maps.Marker({ element: el }) .setLngLat({ lat: location.point[1], lng: location.point[0] }) .addTo(nbmap.map); }); reassignedRouteOptimizationResults.result.routes.forEach((route, idx) => { if (route.vehicle !== selectedVehicle2.vehicle) return; nbmap.map.addSource(`route-${idx}`, { type: "geojson", data: { type: "Feature", properties: {}, geometry: { type: "LineString", coordinates: nextbillion.utils.polyline .decode(route.geometry) .map((c) => c.reverse()) } } }); nbmap.map.addLayer({ id: `route-${idx}`, type: "line", source: `route-${idx}`, layout: { "line-join": "round", "line-cap": "round" }, paint: { "line-color": colors[idx], "line-width": 4 } }); }); }); }37:Tcad,// async function getData(city, nPoints, nRegions, nVehiclesPerRegion) { // const url = `https://m4aqpzp5ah6n7ilzunwyo5ma2u0ezqcc.lambda-url.us-east-2.on.aws/?region=${city}&number=${ // nPoints + 10 // }&vehicles=${nRegions * nVehiclesPerRegion}&type=darp`; // const response = await fetch(url); // const json = await response.json(); // console.log(json.pointsArray.length); // 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); // let pointIdx = 0; // while (pointIdx < nPoints) { // const point = json.pointsArray[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, // }); // pointIdx++; // 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 ${veh_idx}`, // id: veh_idx, // license: json.vehicleArray.at(veh_idx++)?.license, // region: r_idx, // skills, // }); // 1; // } // }); // console.log({ // locations: locations.length, // vehicles: vehicles.length, // regions: regions.length, // points: points.length, // }); // return { // locations, // vehicles, // regions, // }; // };38:T9f1,async function getData(city, nPoints, nRegions, nVehiclesPerRegion) { const url = `https://m4aqpzp5ah6n7ilzunwyo5ma2u0ezqcc.lambda-url.us-east-2.on.aws/?region=${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 ${veh_idx}`, id: veh_idx, license: json.vehicleArray.at(veh_idx++)?.license, region: r_idx, skills }); 1; } }); return { locations, vehicles, regions }; }39:T51c,function getMVRPInputs(locations, vehicles) { const _locations = []; _locations.push(transformPoint(depot.point), transformPoint(recycling.point)); let locationIndex = 2; let pickupId = 0; let deliveryId = 0; const shipments = []; for (const location of locations) { _locations.push(transformPoint(location.point)); shipments.push({ amount: [wasteVolume[location.type]], priority: priorities[location.type], pickup: { location_index: locationIndex++, id: pickupId++, time_windows: [[shiftStartTime, shiftEndTime]], service: 100 }, delivery: { location_index: 1, id: deliveryId++, time_windows: [[shiftStartTime, shiftEndTime]] }, priority: priorities[location.type], skills: location.skills }); } // debugger; const _vehicles = []; for (const vehicle of vehicles) { _vehicles.push({ id: vehicle.id, capacity: [truckCapacity], depot: 0, start_index: 0, end_index: 0, time_window: [shiftStartTime, shiftEndTime], skills: vehicle.skills }); } return { depots: [{ id: 0, location_index: 0 }], locations: { id: 1, location: _locations.join("|") }, shipments, vehicles: _vehicles }; }3a:[] 2f:{"id":"75e762c6ce56459e","slug":null,"title":"Waste Collection Route Optimization (main)","thumbnail":"c4c1101f4763f0c4547dc2170025280929ac642b7c2e4f53310848e0d9fa50ae","access_level":"public","create_time":"$D2023-07-10T13:04:53.149Z","update_time":"$D2023-07-10T13:22:31.605Z","view_time":null,"first_public_time":"$D2023-07-10T13:06:35.882Z","has_unpublished_edits":null,"fork":{"id":"1efddb7ec04d415f","slug":"waste-collection-route-optimization-main","title":"Waste Collection Route Optimization (main)","owner":{"id":"787ce1766e2f8353","login":"texoslab","name":"Texoport's Workspace"}},"stars":0,"starred":false,"owner":{"type":"team","id":"99d73f2cc58ce195","login":"shweta-singh-ws","name":"Shweta Singh's Workspace","avatar_url":"https://avatars-next.observableusercontent.com/0f5b76fb1685c49c1e920b0718155b26ce0a42e789f5b163ef8c5680762f72f2","tier":"starter_2024"},"version":3206,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"0712814f58bfd135","login":"shweta-singh","name":"Shweta Singh","avatar_url":"https://avatars-next.observableusercontent.com/8129d4d485e9294aa796cb665849f7699cd5ae4b404d8dc8ab660ebba02a2289","tier":null}],"members":[{"type":"individual","id":"0712814f58bfd135","login":"shweta-singh","name":"Shweta Singh","avatar_url":"https://avatars-next.observableusercontent.com/8129d4d485e9294aa796cb665849f7699cd5ae4b404d8dc8ab660ebba02a2289","tier":null,"role":"editor"},{"type":"team","id":"99d73f2cc58ce195","login":"shweta-singh-ws","name":"Shweta Singh's Workspace","avatar_url":"https://avatars-next.observableusercontent.com/0f5b76fb1685c49c1e920b0718155b26ce0a42e789f5b163ef8c5680762f72f2","tier":"starter_2024","role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":1,"collection":null,"type":"notebook","body":{"title":"Waste Collection Route Optimization (main)","cells":[{"id":0,"value":"# Waste Collection Route Optimization (main)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1951,"value":"## Background\nIn this notebook, we use several of NextBillion.ai's products, including the Route Optimization API and the Web Maps SDK, to provide a solution to the Waste Collection Route Optimization problem. ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1953,"value":"md`\n## Problem Statement\nThe problem at hand involves a waste collection agency that operates out of a single depot in a chosen city, handling **${\n inputs.nPoints\n}** waste bins in **${\n inputs.nRegions\n} regions** on a given day. The start time is **${dateFns.format(\n new Date(shiftStartTime * 2000),\n \"hh:mm\"\n)}** and the shift duration is **${\n inputs.shiftDuration\n} hours**. Each truck has a capacity, by volume, of **${truckCapacity} cubic meters**. There are three types of waste to be collected: *solid*, *organic*, and *medical*, and it can be collected from three types of locations, *residential*, *commercial*, and *hospitals*.\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1969,"value":"$31","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1976,"value":"md`\n## Constraints\nFor the sake of simplicity, we make the following assumptions in this solution. Please note that the Route Optimization API can handle more complex scenarios:\n* All vehicles have the same capacity of ${truckCapacity} cubic meters\n* We only take into account the volume of waste and not the weight. However, the Route Optimization API can handle multi-dimensional quantities as stated in the documentation.\n* Initially, all regions in the given city are assigned the same number of vehicles.\n\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1979,"value":"htl.html`Note: this demo has the possibility of generating a large number of Route Optimization transactions against the key being used and should only be used with evaluation/demo API keys.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1985,"value":"## Parameters\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":15,"value":"viewof apiKey = secret2(\"apiKey\", {\n title: \"NextBillion.ai API Key\",\n submit: \"Set\",\n description:\n \"Contact support@nextbillion.ai to get your API key\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3188,"value":"cities","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":68,"value":"$32","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":724,"value":"viewof showBins = Inputs.checkbox([\"residential\", \"commercial\", \"hospital\"], {\n label: \"Types of bins to show\",\n value: [\"residential\", \"commercial\", \"medical\"]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1941,"value":"### Vehicles Table","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":3176,"value":"The following table denotes the number of vehicles that were assigned (and not assigned) jobs after the first round of Route Optimization\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":3153,"value":"{\n const result = initialRouteOptimizationResult;\n const assignedVehicles = result.flatMap((r) =>\n r.result.routes.map((route) => route.vehicle)\n );\n const unassignedVehicles = vehicles.filter(\n (v) => !assignedVehicles.includes(v.id)\n );\n\n return md`\n\n| Vehicle Status | quantity |\n|------------|-----------------------------------|\n| Assigned | ${assignedVehicles.length} |\n| Not assigned | ${unassignedVehicles.length} |\n\n`;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1720,"value":"vehiclesTable","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1987,"value":"md`\n## Randomly Generated Data\nThe following map displays the random locations we generate, along with the regions they are a part of. \nResidential properties are represented by ${icons.residential}, commercial properties by ${icons.commercial}, hospitals by ${icons.medical}, the recycling center by ${icons.recycling}, and the depot by ${icons.depot}\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":999,"value":"{\n const container = html`\n

\n `;\n yield container;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1593,"value":"$35","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2448,"value":"**Select a truck below to view its sequence of pickups**","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":2430,"value":"viewof selectedVehicle1 = Inputs.select(\n initialRouteOptimizationResult.flatMap((r) => r.result.routes),\n {\n format: (x) => `Truck ${x.vehicle}`\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2454,"value":"selectedVehicle1Table = {\n const rows = [];\n\n selectedVehicle1.steps.forEach((step) => {\n if (step.type !== \"delivery\" && step.type !== \"end\") {\n rows.push({\n Arrival: formatTime(step.arrival),\n Type: _.capitalize(step.type),\n \"Service Time (minutes)\": `${step.service / 100} minutes`,\n Load: step.load[0]\n });\n }\n });\n\n const recyclingStep = selectedVehicle1.steps.find(\n (s) => s.type === \"delivery\"\n );\n rows.push({\n Arrival: formatTime(recyclingStep.arrival),\n Type: \"Recycling\",\n \"Service Time (minutes)\": \"10 minutes\"\n });\n rows.push({\n Arrival: formatTime(selectedVehicle1.steps.at(-1).arrival),\n Type: \"End\",\n \"Service Time (minutes)\": \"-\"\n });\n\n return rows;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2471,"value":"selectedVehicle1Table","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":2672,"value":"initialOptimizationResultTable = initialRouteOptimizationResult.map(\n (r, idx) => {\n const nUnassigned = r.result.summary.unassigned / 2;\n const nAssignedTrucks = r.result.routes.length;\n const nUnassignedTrucks = inputs.nVehiclesPerRegion - nAssignedTrucks;\n console.log(r.result);\n return {\n Region: `Region ${idx}`,\n \"Unserviceable bins\": nUnassigned,\n \"Serviceable bins\": r.result.routes\n .flatMap((route) => route.steps)\n .filter((route) => route.type === \"pickup\").length,\n \"No: Assigned Trucks\": nAssignedTrucks,\n \"No: Unassigned Trucks\": nUnassignedTrucks\n };\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2683,"value":"initialOptimizationResultTable","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":2510,"value":"md`\n## Dealing with unassigned bins\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2286,"value":"{\n const nBins =\n locations.length % 10 === 0 ? locations.length : locations.length + 1;\n if (unassignedBins.length === 0)\n return md`All bins were successfully assigned`;\n else\n return md`Out of the **${nBins} bins**, **${unassignedBins.length}** were unassigned, which could be assigned to **${unassignedVehicles.length} trucks**. We now attempt to reassign them by running yet another Route Optimization API call with the remaining bins and trucks.`;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2213,"value":"unassignedBins = {\n let unassignedBins = [];\n for (let result of initialRouteOptimizationResult) {\n if (result.result.summary.unassigned > 0) {\n // result.summary.unassigned records each location twice, once for pickup, and the other for delivery, so we avoid duplicates\n const locs = result.result.unassigned.filter((_, idx) => idx % 2 == 0);\n locs.forEach((loc) => {\n if (_.keys(locationsMap.get(loc.id)).includes(\"point\")) {\n unassignedBins.push(locationsMap.get(loc.id));\n }\n });\n }\n }\n return unassignedBins;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2211,"value":"unassignedVehicles = {\n const assignedVehicleIds = [];\n initialRouteOptimizationResult.forEach((route) => {\n assignedVehicleIds.push(...route.result.routes.map((r) => r.vehicle));\n });\n\n return _.difference(\n vehicles.map((v) => v.id),\n assignedVehicleIds\n ).map((id) => vehiclesMap.get(id));\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2305,"value":"reassignedRouteOptimizationResults = {\n const mvrpData = getMVRPInputs(unassignedBins, unassignedVehicles);\n const result = await mvrp(mvrpData, {\n objective: {\n travel_cost: \"distance\"\n }\n });\n return result;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2367,"value":"{\n if (unassignedBins.length === 0) return \"\";\n const result = reassignedRouteOptimizationResults.result;\n const nReassignedTrucks =\n reassignedRouteOptimizationResults.result.routes.length;\n const nUnassigned = result.summary.unassigned;\n const nReassigned = unassignedBins.length - nUnassigned;\n const nVehicles = result.routes.length;\n\n if (nUnassigned === 0) {\n const trucks = nVehicles === 1 ? \"1 truck\" : `${nVehicles} trucks`;\n return md`After running the Route Optimization API, *all* of the unassigned bins were reassigned to **${trucks}**`;\n } else {\n return md`After running the Route Optimization API, **${nReassigned}** of the **${unassignedBins.length}** bins were reassigned to **${nReassignedTrucks}** trucks`;\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2548,"value":"viewof selectedVehicle2 = Inputs.select(\n reassignedRouteOptimizationResults.result.routes,\n {\n format: (route) => `Truck ${route.vehicle}`\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2392,"value":"$36","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2561,"value":"**Select a truck below to view its assigned delivery route**","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":2554,"value":"selectedVehicle2Table = {\n const rows = [];\n\n selectedVehicle2.steps.forEach((step) => {\n if (step.type !== \"delivery\" && step.type !== \"end\") {\n rows.push({\n Arrival: formatTime(step.arrival),\n Type: _.capitalize(step.type),\n \"Service Time (minutes)\": step.service / 100\n });\n }\n });\n\n const recyclingStep = selectedVehicle2.steps.find(\n (s) => s.type === \"delivery\"\n );\n rows.push({\n Arrival: formatTime(recyclingStep.arrival),\n Type: \"Recycling\",\n \"Service Time (minutes)\": NaN\n });\n rows.push({\n Arrival: formatTime(selectedVehicle2.steps.at(-1).arrival),\n Type: \"End\",\n \"Service Time (minutes)\": NaN\n });\n\n return rows;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2556,"value":"selectedVehicle2Table","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":2630,"value":"### Result","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":2870,"value":"reassignResult = {\n const result = reassignedRouteOptimizationResults.result;\n const nUnassigned = result.summary.unassigned;\n const nReassigned = unassignedBins.length - nUnassigned;\n const nVehicles = result.routes.length;\n\n return { nUnassigned, nReassigned, nVehicles };\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2851,"value":"| | Unserviceable Bins | Unassigned Vehicles |\n| ------------------ | ----------------------------- | ------------------------------------------------------- |\n| Initial Assignment | ${unassignedBins.length} | ${unassignedVehicles.length} |\n| After Reassignment | ${reassignResult.nUnassigned} | ${unassignedVehicles.length - reassignResult.nVehicles} |","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":2884,"value":"vehicles.length - (unassignedVehicles.length + reassignResult.nVehicles)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":59,"value":"### Helper Functions","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1304,"value":"async function mvrp(\n data,\n options = {\n objective: {\n minimise_num_depots: false,\n travel_cost: \"distance\"\n }\n }\n) {\n const optimizeRequest = await axios\n .post(`https://api.nextbillion.io/optimise-mvrp?` + `key=${apiKey}`, {\n ...data,\n options\n })\n .then((res) => res.data);\n\n const mvrpRequestId = optimizeRequest.id;\n let attempts = 0;\n\n while (attempts < 10) {\n const result = await axios({\n url: `https://api.nextbillion.io/optimise-mvrp/result?id=${mvrpRequestId}&key=${apiKey}`,\n method: \"GET\",\n headers: {}\n });\n\n if (\n result.data &&\n result.data.status === \"Ok\" &&\n result.data.message == \"\"\n ) {\n return result.data;\n }\n attempts++;\n await new Promise((resolve) => setTimeout(resolve, 5 * 1000));\n }\n}","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1186,"value":"function transformPoint(p) {\n return [p[1], p[0]].join(\",\");\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3102,"value":"$37","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":918,"value":"$38","pinned":false,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":402,"value":"function getRegions(points, count) {\n const extreme = findExtremeCoordinates(points);\n const bounds = [...extreme[0], ...extreme[1]];\n const rest = points.filter((point) => {\n return (point[0] === extreme[0][0] && point[1] === extreme[0][1]) ||\n (point[0] === extreme[1][0] && point[1] === extreme[1][1])\n ? false\n : true;\n });\n\n const sampledPoints = _.sampleSize(rest, count - 2);\n sampledPoints.push(...extreme);\n\n const delaunay = d3Delaunay.Delaunay.from(sampledPoints);\n const voronoi = delaunay.voronoi(bounds);\n\n const regions = [];\n for (let point of voronoi.cellPolygons()) {\n regions.push({\n polygon: turf.lineToPolygon(turf.lineString(point)),\n color: colors[regions.length]\n });\n }\n\n return regions;\n}","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":985,"value":"function createMap(id, center, zoom = 10) {\n const nbmap = new nextbillion.maps.Map({\n container: document.getElementById(id),\n center: {\n lat: center[1],\n lng: center[0]\n },\n zoom,\n maxZoom: 15,\n minZoom: 0,\n style: \"https://api.nextbillion.io/maps/streets/style.json\",\n scrollZoom: true\n });\n\n return nbmap;\n}","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2467,"value":"function formatTime(time) {\n return dateFns.format(new Date(time * 2000), \"hh:mm\");\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":542,"value":"### Variables","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":2026,"value":"locationsMap = {\n const locationsMap = new Map();\n locations.forEach((loc, idx) => {\n locationsMap.set(idx + 2, loc);\n });\n return locationsMap;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2261,"value":"vehiclesMap = {\n const vehiclesMap = new Map();\n vehicles.forEach((vehicle, idx) => {\n vehiclesMap.set(idx, vehicle);\n });\n\n return vehiclesMap;\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":921,"value":"data = getData(\n 'la',\n inputs.nPoints + 2,\n inputs.nRegions,\n inputs.nVehiclesPerRegion\n)","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":546,"value":"allLocations = data.locations","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":940,"value":"vehicles = data.vehicles","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1715,"value":"vehiclesTable = {\n const vehiclesAssignedInitially = Object.fromEntries(\n initialRouteOptimizationResult.flatMap((r) =>\n r.result.routes.map((route) => [\n route.vehicle,\n route.steps.filter((step) => step.type === \"pickup\").length\n ])\n )\n );\n return vehicles.map((vehicle) => ({\n name: vehicle.name,\n license: vehicle.license,\n solid: vehicle.skills.includes(0) ? \"Yes\" : \"No\",\n organic: vehicle.skills.includes(1) ? \"Yes\" : \"No\",\n medical: vehicle.skills.includes(2) ? \"Yes\" : \"No\",\n \"# Jobs Assigned\": vehiclesAssignedInitially[vehicle.id] ?? 0\n }));\n}","pinned":false,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1921,"value":"locationsTable = locations.map((l) => ({\n Name: l.name,\n Location: `${l.point.map((ax) => _.round(ax, 5)).join(\", \")}`,\n Type: _.capitalize(l.type),\n Region: l.regionId,\n \"Solid waste\": l.skills.includes(0) ? \"Yes\" : \"No\",\n \"Organic waste\": l.skills.includes(1) ? \"Yes\" : \"No\",\n \"Medical waste\": l.skills.includes(2) ? \"Yes\" : \"No\"\n}))","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1876,"value":"regions = data.regions","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":551,"value":"depot = allLocations[0]","pinned":false,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":555,"value":"recycling = allLocations[1]","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1246,"value":"locations = allLocations.slice(2)","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":604,"value":"centroid = {\n const point = city.centroid.split(\",\");\n return [point[1], point[0]];\n}","pinned":false,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3192,"value":"city = cities.find(c => c.value === 'la')","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":485,"value":"### Constants","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":2412,"value":"truckCapacity = 100","pinned":false,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":386,"value":"RESIDENTIAL_PERCENT = 0.7","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":391,"value":"COMMERCIAL_PERCENT = 0.25","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":393,"value":"HOSPITAL_PERCENT = 0.05","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1396,"value":"shiftStartTime = inputs.shiftStart.getTime() / 1000","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1398,"value":"shiftEndTime = dateFns\n .addHours(inputs.shiftStart, inputs.shiftDuration)\n .getTime() / 1000","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":35,"value":"skills = {\n return {\n solid: 0,\n organic: 1,\n medical: 2\n };\n}","pinned":false,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":823,"value":"priorities = {\n return {\n residential: 0,\n commercial: 1,\n medical: 2\n };\n}","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":128,"value":"icons = {\n return {\n residential: \"🏠\",\n commercial: \"🏪\",\n medical: \"🏥\",\n trash: \"🗑️\",\n depot: \"🏭\",\n recycling: \"♻️\"\n };\n}","pinned":false,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":857,"value":"wasteVolume = {\n return {\n residential: 5,\n commercial: 20,\n medical: 30\n };\n}","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":74,"value":"### Dependencies","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1300,"value":"$39","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":445,"value":"turf = require(\"https://unpkg.com/@turf/turf@6/turf.min.js\")","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3179,"value":"cities = [\n { name: \"Los Angeles\", centroid: \"34.01645908,-117.8443661\", value: \"la\" },\n {\n name: \"Columbus\",\n centroid: \"39.96348377548454,-83.00164743045242\",\n value: \"columbus\"\n },\n { name: \"Las Vegas\", centroid: \"36.09523509,-115.17273704\", value: \"lv\" }\n]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":98,"value":"import {\n guard,\n colors,\n renderPolygon,\n d3Delaunay,\n findExtremeCoordinates\n} from \"@texoslab/nbai-helpers\"","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":8,"value":"import {\n nextbillion,\n secret2,\n styles,\n routeStyles\n} from \"@nbai/nextbillion-ai-dependencies\"","pinned":false,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":208,"value":"","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":20,"value":"nextbillion.setApiKey(apiKey)","pinned":false,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1149,"value":"axios = {\n let axios = await require(\"axios\");\n return axios;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1394,"value":"dateFns = await require(\"https://cdnjs.cloudflare.com/ajax/libs/date-fns/1.30.1/date_fns.js\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":202,"value":"html`Add the stylesheet for the NB.ai SDK
<link href=\"https://maps-gl.nextbillion.io/maps/v2/api/css\" rel=\"stylesheet\">`","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W3a","stdlib":"1","titling":"auto"}} 30:"$2f:body"