31:T7f5,tempMVRPProblem = { if (inputData_a) { let location = ""; let loc_index = 0; let shipments = []; let jobs = []; let vehicles = []; let locations = []; // Delivery use case has pickup and dropoffs that are // associated with 'shipments' - a pickup must occur before // it can be dropped off. if (panel.useCase.value === "delivery") { randomVRPInputs.pointsArray.forEach((p) => { let shipment = { pickup: { id: p.id, description: p.name, location_index: loc_index++, service: parseInt(inputData_a.serviceTime) }, delivery: { id: p.id, description: p.business, location_index: loc_index++, service: parseInt(inputData_a.serviceTime) }, amount: [1] }; shipments.push(shipment); locations.push(`${p.pickup_latitude},${p.pickup_longitude}`); locations.push(`${p.dropoff_latitude},${p.dropoff_longitude}`); }); } else { randomVRPInputs.pointsArray.forEach((j) => { let job = { id: j.id, description: j.business, location_index: loc_index++, service: parseInt(inputData_a.serviceTime) }; jobs.push(job); locations.push(`j.latitude,j.longitude`); }); } randomVRPInputs.vehicleArray.forEach((f) => { locations.push(`${f.latitude},${f.longitude}`); let vehicle = { id: f.id, description: f.vin, start_index: loc_index, end_index: loc_index++, time_window: [ Date.parse(inputData_a.shiftStart) / 1000, Date.parse(inputData_a.shiftEnd) / 1000 ], capacity: [f.capacity], skills: f.attr3 }; vehicles.push(vehicle); }); return { location: location, locations: locations, location_index: loc_index, shipments: shipments, jobs: jobs, vehicles: vehicles }; } }32:T651,inputs = { const offset = new Date().getTimezoneOffset(); let newBase = new Date(new Date().getTime() + 86400 * 1000); let tmrwStart = new Date( `${newBase.toLocaleDateString("en-US")} 06:00:00 GMT${ offset >= 0 ? "+" : "" }${Math.round(offset / 60)}${ Math.abs(offset % 60) ? Math.abs(offset % 60) : "" }` ); let tmrwEnd = new Date( `${newBase.toLocaleDateString("en-US")} 09:00:00 GMT${ offset >= 0 ? "+" : "" }${Math.round(offset / 60)}${ Math.abs(offset % 60) ? Math.abs(offset % 60) : "" }` ); const inputs = { city: Inputs.select(cities, { label: "Select city", format: (x) => x.name, value: cities.find((t) => t.name === "Los Angeles") }), jobs: Inputs.select(jobs, { label: "Number of jobs", value: "25" }), vehicles: Inputs.select(vehicles, { label: "Number of vehicles", value: "10" }), shiftStart: Inputs.datetime({ label: "Shift Start", value: tmrwStart.toISOString().slice(0, -1) }), shiftEnd: Inputs.datetime({ label: "Shift End", value: `${tmrwEnd.toISOString().slice(0, -1)}` }), useCase: Inputs.select(useCases, { label: "Use Case", format: (x) => x.name, value: useCases.find((t) => t.name === "service") }), objectiveFunction: Inputs.select(objectives, { label: "Objective Function", format: (x) => x.name, value: objectives.find((t) => t.name === "Minimize Time") }), serviceTime: Inputs.text({ label: "Service Time at Each Stop", value: "300" }) }; return inputs; }33:T4c6,routesGeoJson = { let routesGeoJson = { type: 'FeatureCollection', features: [] }; // we create a geojson object to send to our mapview elements // It will be a feature collection of all the route polylines checkStatus.result.routes.forEach((rte,idx) => { //console.log(rte); let feature = { type: 'Feature', properties: { id: rte.vehicle, vin: rte.description }, geometry: { coordinates: nextbillion.utils.polyline.decode(rte.geometry,5) .map((c) => c.reverse()), type: 'LineString' } } routesGeoJson.features.push(feature); rte.steps.forEach((st,stIdx) => { let stop = { type: 'Feature', properties: { id: rte.vehicle, vin: rte.description, description: st.description, stop_idx: stIdx, arrival: st.arrival, type: st.type, pointType: ((st.type == "start"|st.type == "end")?16:255) }, geometry: { coordinates: [st.location[1],st.location[0]], type: 'Point' } } routesGeoJson.features.push(stop); }) }); console.log(routesGeoJson); return routesGeoJson; }34:[] 2f:{"title":"Example Route Optimization Problem","cells":[{"id":0,"value":"![text](https://d12qcqjlhp2ahm.cloudfront.net/maps-logo.svg) \n# Example Route Optimization Problem ","pinned":false,"hidden":false,"mode":"md"},{"id":1935,"value":"toc(\"h2, h3, h4\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":508,"value":"### Background\nNextBillion's Route Optimization API provides a sophisticated interface for managing a list of orders/jobs/tasks with locations and creating the optimal, most efficient routes.\n

\nIn this tutorial, we'll guide you through the steps that you can take to build, solve, and visualize complex multi-vehicle routing problem solutions.\n

\nRefer to the API documentation at this page for more supporting details: [API doc](https://docs.nextbillion.ai/docs/navigation/api/optimization-mvrp)\n

Note: this demo has the possibility of generating a large number of MVRP transactions against the key being used and should only be used with evaluation/demo API keys.\n","pinned":false,"hidden":false,"mode":"md"},{"id":1189,"value":"viewof apiKey = secret2(\"apiKey\", {\n title: \"NextBillion.ai API Key\",\n submit: \"Set\",\n description: \"Contact support@nextbillion.ai to get your API key\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1934,"value":"{\n nextbillion.setApiKey(apiKey);\n return html`Set API key
nextbillion.setApiKey(${apiKey.substr(0,4)}....)`;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":525,"value":"### Initial Setup\nIn this section we will set some initial parameters that are used to formulate the inputs to the MVRP solver. The `NB.ai API KEY` is necessary to interact with the MVRP services and it should be entered first to activate the tutorial tasks.\n

\nNext modify the other parameters according to the problem that you want to create: City Selection, Number of Jobs, Use Case, Objective Function and the Shift definitions.\n

\nThe use case descriptions are as follows:\n\n- Delivery: we will define pickup and delivery/drop-off locations. A vehicle is assigned a manifest that will include a sequence of pickup and drop-offs. The vehicle has a set capacity of 3 and each pickup comprises 1 item/person.\n- Service Worker: we will define individual service locations that require a worker/vehicle to dispatch to the location.","pinned":false,"hidden":false,"mode":"md"},{"id":1234,"value":"---\n","pinned":false,"hidden":false,"mode":"md"},{"id":1451,"value":"viewof panel = Inputs.form(inputs, {template: v => htl.html`\n

\n ${v.city}\n ${v.jobs}\n ${v.vehicles}\n ${v.shiftStart}\n ${v.shiftEnd}\n ${v.useCase}\n ${v.objectiveFunction}\n ${v.serviceTime}\n

\n\n`})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1566,"value":"{\n const button = html` `;\n button.onclick = () => {\n mutable inputData_a = panel;\n button.disabled = true; \n }\n return html`${button}`;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2173,"value":"inputData_a.city","pinned":true,"hidden":false,"mode":"ojs"},{"id":1236,"value":"---\n","pinned":false,"hidden":false,"mode":"md"},{"id":534,"value":"{\n return html`

${md`### Random Data Generation\nLet's start with the retrieval of random vehicle and pickup/dropoff data for the city that was selected. The random data will contain the requested number of jobs and each will consist of a pickup and drop-off point. Feel free to browse the object to see the pickup/dropoff content. Green points are vehicles and red points are stops/jobs.`}

`;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":964,"value":"{\n if (!apiKey && randomVRPInputs) {\n return geoviewer(randomVRPInputs.vehGeoJson, {\n width: 750,\n height: 450,\n col: \"#8058a0\",\n fillOpacity: 0.9,\n lineWidth: 5,\n style: \"positron\"\n });\n } else {\n if (randomVRPInputs) {\n return geoviewer(randomVRPInputs.vehGeoJson, {\n width: 750,\n height: 450,\n col: \"#8058a0\",\n fillOpacity: 0.9,\n lineWidth: 5,\n style: \"nbai\",\n apiKey: apiKey\n });\n }\n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1912,"value":"randomVRPInputs = {\n let retval = null;\n retval = await fetch(\n `https://m4aqpzp5ah6n7ilzunwyo5ma2u0ezqcc.lambda-url.us-east-2.on.aws/?region=${\n inputData_a.city.value\n }&number=${inputData_a.jobs}&vehicles=${inputData_a.vehicles}&type=${\n inputData_a.useCase.value === \"delivery\" ? \"darp\" : \"service\"\n }`\n ).then((response) => response.json());\n\n return retval;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2160,"value":"csvOut = {\n const headers = Object.keys(randomVRPInputs.vehicleArray[0]);\n const rows = randomVRPInputs.vehicleArray.map((row) =>\n headers.map((field) => JSON.stringify(row[field] || \"\")).join(\",\")\n );\n return [headers.join(\",\"), ...rows].join(\"\\n\");\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":206,"value":"---\n### Build the Problem Inputs\nWe start to build the needed JSON objects that will eventually be submitted to the MVRP endpoint. In this section, we are building the `shipments` which each consist of random pickup and dropoff locations in the city region _or_ the service worker `jobs`. We also create the list of locations that will be referenced by index. Browse the temporary object that will be used further down the page to create the final input object. You can also expand the block to see the Javascript code that created the temporary object.\n\n","pinned":false,"hidden":false,"mode":"md"},{"id":190,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":594,"value":"---\n### Submit the Problem to the Route Optimization API Endpoint\nWe are now to the point where we can put together the full Route Optimization request containing all of our locations, shipment details (pickup/drop-off), vehicles, and options for the solution.\n

\nThe Route Optimization endpoint is a non-blocking/asynchronous endpoint. We will receive back a reference ID for the optimization job and a status message as seen below. We've highlighted the reference ID in green.\n

\nNote: if you see an error in this section, more than likely you have an invalid API Key set in the input box above. \n","pinned":false,"hidden":false,"mode":"md"},{"id":221,"value":"mvrpID = {\n let locations = Object({\n id: 1,\n location: tempMVRPProblem.locations\n });\n\n let url = `https://api.nextbillion.io/optimization/v2?key=${apiKey}`;\n let bodyData = {\n description: `MVRP Tutorial ${new Date().toISOString()}`,\n locations: {\n id: 2,\n location: tempMVRPProblem.locations\n },\n // set shipments information\n shipments: tempMVRPProblem.shipments,\n // set vehicles information\n vehicles: tempMVRPProblem.vehicles,\n jobs: tempMVRPProblem.jobs,\n options: {\n travel_cost: inputs.objectiveFunction.value.value,\n minimise_num_depots: false\n }\n };\n const response = await fetch(url, {\n method: \"POST\",\n headers: {\n \"Content-Type\": \"application/json\"\n },\n body: JSON.stringify(bodyData)\n });\n return response.json();\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":348,"value":"viewof jobID = htl.html`
Route Optimization Request ID: ${\n mvrpID ? mvrpID.id : mvrpID\n}
`","pinned":false,"hidden":false,"mode":"ojs"},{"id":601,"value":"---\n### Retrieve Route Optimization Result\nOnce we have the reference ID for the Route Optimization request, we can poll the Route Optimization status endpoint to get the solution. In this tutorial, we are waiting 10 seconds before polling for the solution. When you see a status message of `Ok` you can browse the result to see the optimized routing solution.\n

\nNote: if you see an error in this section, more than likely you have an invalid API Key set in the input box above or the API key is not valid for the city region selected.","pinned":false,"hidden":false,"mode":"md"},{"id":720,"value":"html`
If you get a status message indicating Job still processing just wait a few seconds and press this button.

${viewof requestResult}`","pinned":false,"hidden":false,"mode":"ojs"},{"id":242,"value":"checkStatus = {\n mvrpID;\n requestResult;\n let url = `https://api.nextbillion.io/optimization/v2/result?key=${apiKey}&id=${mvrpID.id}`;\n let retval = null;\n\n yield Promises.delay(5000).then(() => {\n retval = fetch(url).then((response) => response.json());\n return retval;\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":631,"value":"kpiStats = {\n let deliveryCount = 0;\n checkStatus.result.routes.forEach((rte, rteidx) => {\n rte.steps.forEach((step, index) => {\n if (step.id && step.id != 99) {\n ++deliveryCount;\n }\n });\n });\n return {\n totalDistance: `${(checkStatus.result.summary.distance/1000).toFixed(1)} km`,\n totalTime: `${(checkStatus.result.summary.duration/60).toFixed(1)} mn`,\n nbrRoutes: checkStatus.result.summary.routes,\n avgStops: (deliveryCount/checkStatus.result.summary.routes).toFixed(1)\n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":645,"value":"| KPI | Value |\n| ------ | -------- |\n| Total Distance | ${kpiStats.totalDistance} |\n| Total Time | ${kpiStats.totalTime} |\n| Number of Routes | ${kpiStats.nbrRoutes} |\n| Average Stops Per Vehicle | ${kpiStats.avgStops}|","pinned":false,"hidden":false,"mode":"md"},{"id":605,"value":"---\n### Render Solution on a Map\n\n","pinned":false,"hidden":false,"mode":"md"},{"id":1261,"value":"viewof routeSelector = Inputs.select(routesGeoJson.features.filter(f => f.geometry.type === 'LineString'), {multiple: false, label: \"Select route to view\", format: x => x.properties.vin, value: t => t.properties.vin})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1676,"value":"green marker is the vehicle start location and red markers are stop locations.","pinned":false,"hidden":false,"mode":"md"},{"id":997,"value":"{\n return geoviewer(routesFiltered, {width:550,height:550,col:'#8058a0',fillOpacity:.9,lineWidth:3,style:'nbai',apiKey:apiKey});\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1862,"value":"Inputs.table(selectedRoute[0].steps, {\n columns: [\"type\", \"arrival\", \"load\", \"description\", \"duration\"],\n header: {\n type: \"Task\",\n arrival: \"Arrival Time\",\n load: \"Nbr Loaded\",\n description: \"Account\",\n duration: \"Duration\"\n },\n width: {\n type: 80,\n arrival: 120,\n load: 60,\n duration: 100\n },\n format: {\n type: (x) => x.toUpperCase(),\n arrival: (x) =>\n new Date(x * 1000).toLocaleTimeString([], {\n hour: \"2-digit\",\n minute: \"2-digit\",\n hour12: false\n }),\n duration: (x) => (x / 60).toFixed(1) + \" mn\"\n },\n rows: 10,\n maxWidth: 600,\n multiple: false,\n required: false\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1898,"value":"selectedRoute = checkStatus.result.routes.filter(f => f.description === routeSelector.properties.vin)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1000,"value":"If you want to visualize the optimized routing solution along with the sequencing of the stops, the NB.ai Optimization Tester tool is available. \n\nNB.AI Route Optimization Playground App (loads the current solution)\n","pinned":false,"hidden":false,"mode":"md"},{"id":341,"value":"### Other Dependencies","pinned":false,"hidden":false,"mode":"md"},{"id":1139,"value":"import { nextbillion, cities, secret2 } from \"@nbai/nextbillion-ai-dependencies\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":352,"value":"styling = html`\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":849,"value":"geoviewer = require(\"https://d12qcqjlhp2ahm.cloudfront.net/nb_geoverview2.js\").then((f) => f.view)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1613,"value":"html`${viewof requestResult}`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1005,"value":"viewof requestResult = Inputs.button(\"Request Result\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":1686,"value":"mutable inputData_a = null","pinned":false,"hidden":false,"mode":"ojs"},{"id":1098,"value":"jobs = [\"5\", \"10\", \"25\", \"50\", \"100\", \"200\", \"500\"]","pinned":false,"hidden":false,"mode":"ojs"},{"id":1111,"value":"vehicles = [\"1\", \"2\", \"10\", \"20\", \"50\", \"100\"]","pinned":false,"hidden":false,"mode":"ojs"},{"id":1163,"value":"useCases = [\n {name: \"Delivery\", value: \"delivery\"},\n {name: \"Service Worker\", value: \"service\"}\n ]","pinned":false,"hidden":false,"mode":"ojs"},{"id":1175,"value":"objectives = [\n {name: \"Minimize Time\", value: \"duration\"},\n {name: \"Minimize Distance\", value: \"distance\"}\n]","pinned":false,"hidden":false,"mode":"ojs"},{"id":1523,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":924,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":1279,"value":"routesFiltered = Object({\n type: 'FeatureCollection',\n features: routesGeoJson.features.filter(f => f.properties.vin === routeSelector.properties.vin)\n});","pinned":false,"hidden":false,"mode":"ojs"},{"id":1931,"value":"import { toc } from \"@nebrius/indented-toc\" // This component generates the Table of Contents","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W34","stdlib":"1","titling":"auto"}

Route Optimization Request ID: ${\n mvrpID ? mvrpID.id : mvrpID\n}