{"id":944,"date":"2026-08-17T06:38:18","date_gmt":"2026-08-17T06:38:18","guid":{"rendered":"https:\/\/trendroute.ai\/?page_id=944"},"modified":"2026-09-07T12:31:44","modified_gmt":"2026-09-07T12:31:44","slug":"sandbox-user-guide","status":"publish","type":"page","link":"https:\/\/trendroute.ai\/en\/sandbox-user-guide\/","title":{"rendered":"Sandbox User Guide"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"944\" class=\"elementor elementor-944\" data-elementor-post-type=\"page\">\n\t\t\t\t<div class=\"elementor-element elementor-element-80b1e3b e-con-full e-flex e-con e-parent\" data-id=\"80b1e3b\" data-element_type=\"container\" data-e-type=\"container\" data-no-translation=\"\">\n\t\t\t\t<div class=\"elementor-element elementor-element-11d1e57 elementor-widget elementor-widget-html\" data-id=\"11d1e57\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div 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#trendroute-sandbox-guide .tr-page{padding:32px 24px 20px;border-radius:16px}\r\n  #trendroute-sandbox-guide .tr-grid.cols-2,#trendroute-sandbox-guide .tr-grid.cols-3,#trendroute-sandbox-guide .tr-final-grid,#trendroute-sandbox-guide .tr-pair-images{grid-template-columns:1fr}\r\n  #trendroute-sandbox-guide .tr-grid .tr-card,#trendroute-sandbox-guide .tr-final-card{border-right:none;border-bottom:1px solid var(--tr-border)!important}\r\n  #trendroute-sandbox-guide .tr-grid .tr-card:last-child,#trendroute-sandbox-guide .tr-final-card:last-child{border-bottom:none!important}\r\n  #trendroute-sandbox-guide .tr-mode-row{grid-template-columns:54px 1fr}\r\n  #trendroute-sandbox-guide .tr-mode-row>div:nth-child(3){grid-column:1\/-1;border-top:1px solid var(--tr-border);border-right:none;padding-left:69px}\r\n  #trendroute-sandbox-guide .tr-mode-row.header>div:nth-child(3){display:none}\r\n  #trendroute-sandbox-guide .tr-mode-row.header{grid-template-columns:54px 1fr}\r\n  #trendroute-sandbox-guide p,#trendroute-sandbox-guide li{font-size:15px}\r\n}\r\n@media (max-width:480px){\r\n  #trendroute-sandbox-guide .tr-page{padding:26px 18px 18px}\r\n  #trendroute-sandbox-guide h1{font-size:34px}\r\n  #trendroute-sandbox-guide h2{font-size:28px}\r\n  #trendroute-sandbox-guide h3{font-size:23px}\r\n  #trendroute-sandbox-guide .tr-subtitle{font-size:21px}\r\n}\r\n<\/style>\r\n\r\n<div id=\"trendroute-sandbox-guide\">\r\n  <div class=\"tr-document\">\r\n\r\n    <section class=\"tr-page tr-hero\">\r\n      <div class=\"tr-brand\">TRENDROUTE.AI<\/div>\r\n      <h1>TrendRoute Sandbox<\/h1>\r\n      <div class=\"tr-subtitle\">Test, compare and challenge advanced route optimisation<\/div>\r\n      <p class=\"tr-lead\">A practical guide to exploring TrendRoute.ai across single-route, multi-route, shipment and dynamic route-extension scenarios.<\/p>\r\n      <div class=\"tr-box\">\r\n        <h4>Built for experimentation<\/h4>\r\n        <p>Use predefined scenarios, create test cases directly on the map, or upload your own routing problems to evaluate how TrendRoute.ai performs on challenges that resemble your operation.<\/p>\r\n      <\/div>\r\n      <img decoding=\"async\" class=\"tr-image tr-hero-image\" src=\"\/wp-content\/uploads\/trendroute-sandbox-guide-assets\/tr-sandbox-01-6f812648.jpg\" alt=\"TrendRoute Sandbox solver comparison and route map\">\r\n      <div class=\"tr-cta\">TEST IT. COMPARE IT. CHALLENGE IT.<\/div>\r\n      <p class=\"tr-note\">Testing and evaluation environment - not for production routing<\/p>\r\n      <div class=\"tr-footer\"><span>TrendRoute.ai | Sandbox Guide<\/span><span>1<\/span><\/div>\r\n    <\/section>\r\n\r\n    <section class=\"tr-page\">\r\n      <h2 class=\"tr-section-title\">1. Introduction<\/h2>\r\n      <p>The TrendRoute Sandbox is an interactive environment designed for logistics, transportation and software teams that want to explore how a modern route optimisation engine behaves on realistic routing problems - before integrating it into production.<\/p>\r\n      <p>Rather than asking users to evaluate TrendRoute.ai based only on product claims, the Sandbox makes optimisation visible, interactive and measurable. Users can work with predefined scenarios, create their own test cases directly on the map, upload their own routing problems, compare alternative optimisation methods, inspect route quality visually, introduce operational constraints, and manually challenge the generated solutions.<\/p>\r\n      <p>The Sandbox covers several routing challenges, from optimising the sequence of stops for a single courier to allocating deliveries across multiple vehicles, handling pickup-and-delivery operations, routing multi-step shipments, and inserting newly arriving parcels into existing recurring routes.<\/p>\r\n      <div class=\"tr-box cyan\">\r\n        <h4>The objective<\/h4>\r\n        <p>Give logistics and technology teams a practical way to test how TrendRoute.ai handles real routing challenges and evaluate the results using measurable operational criteria.<\/p>\r\n      <\/div>\r\n      <div class=\"tr-grid cols-2\">\r\n        <div class=\"tr-card\"><h4>Predefined scenarios<\/h4><p>Start immediately with ready-made examples designed to expose different routing behaviours.<\/p><\/div>\r\n        <div class=\"tr-card\"><h4>Your own test cases<\/h4><p>Upload representative single-route or multi-route problems and benchmark TrendRoute.ai on your own data.<\/p><\/div>\r\n        <div class=\"tr-card\"><h4>Map-based testcase creation<\/h4><p>Build a routing problem visually by pinning a hub and stops directly on the map.<\/p><\/div>\r\n        <div class=\"tr-card\"><h4>Interactive benchmarking<\/h4><p>Compare solvers, inspect route shape, add constraints, reorder routes and explore what changed.<\/p><\/div>\r\n      <\/div>\r\n      <h4 class=\"tr-accent-title\">Explore TrendRoute.ai<\/h4>\r\n      <p>The Sandbox gives teams a low-risk way to explore TrendRoute.ai before considering API integration or production deployment. Start with a predefined scenario, then create or upload your own testcase and see how the engine handles a problem that matters to your operation.<\/p>\r\n      <div class=\"tr-cta\">Test it. Compare it. Challenge it.<\/div>\r\n      <div class=\"tr-footer\"><span>TrendRoute.ai | Sandbox Guide<\/span><span>2<\/span><\/div>\r\n    <\/section>\r\n\r\n    <section class=\"tr-page\">\r\n      <h2 class=\"tr-section-title\">2. Accessing the TrendRoute Sandbox<\/h2>\r\n      <p>The Sandbox is accessible from the Route Optimisation Sandbox button on the TrendRoute.ai website.<\/p>\r\n      <p class=\"tr-small-link\"><a href=\"https:\/\/trendroute.ai\/route-optimisation-sandbox\/\" target=\"_blank\" rel=\"noopener\">Open the TrendRoute Sandbox<\/a><\/p>\r\n      <div class=\"tr-pair-images\">\r\n        <div>\r\n          <img decoding=\"async\" class=\"tr-image\" src=\"\/wp-content\/uploads\/trendroute-sandbox-guide-assets\/tr-sandbox-02-a3bd07bb.jpg\" alt=\"TrendRoute.ai website Route Optimisation Sandbox access\">\r\n          <p class=\"tr-caption\">Access the Sandbox from the TrendRoute.ai website.<\/p>\r\n        <\/div>\r\n        <div>\r\n          <img decoding=\"async\" class=\"tr-image\" src=\"\/wp-content\/uploads\/trendroute-sandbox-guide-assets\/tr-sandbox-03-a86e9545.jpg\" alt=\"TrendRoute Sandbox preview access registration\">\r\n          <p class=\"tr-caption\">First-time preview access and testing-only acknowledgement.<\/p>\r\n        <\/div>\r\n      <\/div>\r\n      <h4 class=\"tr-accent-title\">First-time access<\/h4>\r\n      <p>On the first visit, users register for preview access by providing basic contact and company information and accepting the testing-only conditions. The Sandbox is provided for testing and evaluation and should not be used as a commercial or production routing environment.<\/p>\r\n      <p>After the initial registration, the browser remembers the user through local session\/cookie information, so registration does not normally need to be repeated on every visit from the same browser.<\/p>\r\n      <div class=\"tr-box orange\">\r\n        <h4>Experimentation limits<\/h4>\r\n        <p>User-uploaded test cases are limited to 3 cases per day and 50 cases per month. These limits provide enough room for meaningful evaluation while keeping a clear boundary between Sandbox experimentation and production routing.<\/p>\r\n      <\/div>\r\n      <div class=\"tr-footer\"><span>TrendRoute.ai | Sandbox Guide<\/span><span>3<\/span><\/div>\r\n    <\/section>\r\n\r\n    <section class=\"tr-page\">\r\n      <h2 class=\"tr-section-title\">3. Choose the Routing Challenge You Want to Test<\/h2>\r\n      <p>After entering the Sandbox, users select the routing problem that best represents the scenario they want to explore. Five modes are available, each exposing a different capability of the optimisation engine.<\/p>\r\n      <div class=\"tr-mode-table\">\r\n        <div class=\"tr-mode-row header\"><div class=\"num\"><\/div><div>Routing mode<\/div><div>What it demonstrates<\/div><\/div>\r\n        <div class=\"tr-mode-row\"><div class=\"num\">3.1<\/div><div class=\"mode\">Last Mile - Single Route<\/div><div>Optimise one vehicle route and benchmark route quality against alternative solvers.<\/div><\/div>\r\n        <div class=\"tr-mode-row\"><div class=\"num\">3.2<\/div><div class=\"mode\">Last Mile - Multi Route<\/div><div>Allocate deliveries across multiple vehicles and optimise the complete fleet plan.<\/div><\/div>\r\n        <div class=\"tr-mode-row\"><div class=\"num\">3.3<\/div><div class=\"mode\">Shipment - Pickup &amp; Delivery<\/div><div>Optimise paired pickups and deliveries while preserving pickup-before-delivery precedence.<\/div><\/div>\r\n        <div class=\"tr-mode-row\"><div class=\"num\">3.4<\/div><div class=\"mode\">Shipment - Multi-Step<\/div><div>Route shipments through an optional intermediate location before final delivery.<\/div><\/div>\r\n        <div class=\"tr-mode-row\"><div class=\"num\">3.5<\/div><div class=\"mode\">Static Routes + Dynamic Parcels<\/div><div>Insert new orders into recurring routes and create a new route when existing capacity is insufficient.<\/div><\/div>\r\n      <\/div>\r\n      <img decoding=\"async\" class=\"tr-image\" src=\"\/wp-content\/uploads\/trendroute-sandbox-guide-assets\/tr-sandbox-04-654103f4.jpg\" alt=\"Choose Your Routing Mode interface\">\r\n      <p class=\"tr-caption\">Choose the routing mode that best matches the operational challenge you want to test.<\/p>\r\n      <div class=\"tr-footer\"><span>TrendRoute.ai | Sandbox Guide<\/span><span>4<\/span><\/div>\r\n    <\/section>\r\n\r\n    <section class=\"tr-page\">\r\n      <div class=\"tr-eyebrow\">MAIN BENCHMARKING ENVIRONMENT<\/div>\r\n      <h2 class=\"tr-section-title\">3.1 Last Mile - Single Route Optimisation<\/h2>\r\n      <p>Last Mile - Single Route is the most comprehensive benchmarking area of the TrendRoute Sandbox. A single vehicle starts from a hub and visits a set of delivery stops, and the optimisation problem is to determine an efficient sequence in which those stops should be served.<\/p>\r\n      <p>At first glance this can appear straightforward. In practice, a mathematically short route may still contain zig-zagging, backtracking, crossing edges, repeated visits to the same area, poor geographical progression, or inefficient decisions about when to drive and when to walk.<\/p>\r\n      <h4 class=\"tr-accent-title\">Compare recognised optimisation approaches on the same testcase<\/h4>\r\n      <p>For predefined test cases, users can compare Greedy, OR-Tools, PyVRP, VRoom, TrendRoute V3 and TrendRoute V5 on the same routing problem. Solutions can be inspected on the map and compared numerically in the results table.<\/p>\r\n      <div class=\"tr-box\">\r\n        <h4>A broader question than &quot;Which route is shortest?&quot;<\/h4>\r\n        <p>The Sandbox is designed to help users evaluate which solution produces the strongest combination of distance, travel time, productivity and operationally sensible route shape.<\/p>\r\n      <\/div>\r\n      <img decoding=\"async\" class=\"tr-image\" src=\"\/wp-content\/uploads\/trendroute-sandbox-guide-assets\/tr-sandbox-01-6f812648.jpg\" alt=\"Single Route benchmarking solver comparison and interactive map\">\r\n      <p class=\"tr-caption\">Single Route benchmarking: solver comparison, route metrics and interactive map in one view.<\/p>\r\n      <div class=\"tr-footer\"><span>TrendRoute.ai | Sandbox Guide<\/span><span>5<\/span><\/div>\r\n    <\/section>\r\n\r\n    <section class=\"tr-page\">\r\n      <h2 class=\"tr-section-title\">3.1.1 Create a Testcase in the Way That Suits You<\/h2>\r\n      <p>Users do not have to rely only on TrendRoute-provided examples. The Sandbox supports three convenient ways to create a Single Route experiment.<\/p>\r\n      <div class=\"tr-feature-stack\">\r\n        <div class=\"tr-feature\"><h4>Use a predefined testcase<\/h4><p>Start immediately with a ready-made routing problem and compare the available optimisation methods.<\/p><\/div>\r\n        <div class=\"tr-feature\"><h4>Upload your own testcase<\/h4><p>Use a representative historical or synthetic case to evaluate TrendRoute.ai on a routing problem that resembles your own operation.<\/p><\/div>\r\n        <div class=\"tr-feature\"><h4>Create a testcase directly on the map<\/h4><p>For non-technical users, pin the hub and delivery stops directly on the map without preparing a structured input file.<\/p><\/div>\r\n      <\/div>\r\n      <p>The map-based workflow is especially useful for dispatchers, operations managers and other users who want to experiment with geography without dealing with file formats. Users can choose a hub location, add stops by clicking on the map, and run the optimisation directly.<\/p>\r\n      <div class=\"tr-box cyan\">\r\n        <h4>Upload allowance<\/h4>\r\n        <p>User-uploaded cases are limited to 3 per day and 50 per month. Map-based experimentation and predefined scenarios help users explore the Sandbox without turning it into a production routing environment.<\/p>\r\n      <\/div>\r\n      <div class=\"tr-footer\"><span>TrendRoute.ai | Sandbox Guide<\/span><span>6<\/span><\/div>\r\n    <\/section>\r\n\r\n    <section class=\"tr-page\">\r\n      <h2 class=\"tr-section-title\">3.1.2 Measure More Than Distance<\/h2>\r\n      <p>The Single Route comparison table intentionally goes beyond one headline metric. Route optimisation quality should be evaluated from several operational perspectives.<\/p>\r\n      <div class=\"tr-grid cols-2\">\r\n        <div class=\"tr-card\"><h4>Distance<\/h4><p>Total route distance. Even modest improvements can become significant at fleet scale.<\/p><\/div>\r\n        <div class=\"tr-card\"><h4>Travel time<\/h4><p>Estimated time spent travelling between stops. The shortest route in kilometres is not always the fastest.<\/p><\/div>\r\n        <div class=\"tr-card\"><h4>Service time<\/h4><p>Time spent performing work at stops, kept separate from routing travel time.<\/p><\/div>\r\n        <div class=\"tr-card\"><h4>Total duration<\/h4><p>The complete expected route duration including travel and relevant service components.<\/p><\/div>\r\n        <div class=\"tr-card\"><h4>Stops per hour<\/h4><p>A practical productivity metric showing how efficiently a courier can complete deliveries.<\/p><\/div>\r\n        <div class=\"tr-card\"><h4>Route quality<\/h4><p>A score for the operational shape of the route, complementing conventional distance and duration metrics.<\/p><\/div>\r\n      <\/div>\r\n      <h4 class=\"tr-accent-title\">Route Quality - does the route actually make sense?<\/h4>\r\n      <p>Experienced dispatchers and couriers often recognise poor route shape immediately, even when the numerical distance appears competitive. The Quality Score is designed to capture characteristics such as crossing edges, zig-zagging, backtracking, repeated returns to a previously served area, unnecessary detours and weak geographical coherence.<\/p>\r\n      <p>This is particularly valuable when two solvers produce similar distance or duration but noticeably different route shapes.<\/p>\r\n      <div class=\"tr-footer\"><span>TrendRoute.ai | Sandbox Guide<\/span><span>7<\/span><\/div>\r\n    <\/section>\r\n\r\n    <section class=\"tr-page\">\r\n      <h2 class=\"tr-section-title\">3.1.3 Inspect, Challenge and Understand the Route<\/h2>\r\n      <p>The Sandbox is designed to let users investigate why a route behaves the way it does, not only view a final number.<\/p>\r\n      <div class=\"tr-grid cols-2\">\r\n        <div class=\"tr-card\"><h4>Light View \/ Map View<\/h4><p>Switch between a simplified visualisation for analysing route shape and a richer map view for road and geographical context.<\/p><\/div>\r\n        <div class=\"tr-card\"><h4>Show Direction<\/h4><p>Display the real navigable path between consecutive stops instead of relying only on straight-line connections.<\/p><\/div>\r\n        <div class=\"tr-card\"><h4>Matrix Mode<\/h4><p>Inspect Haversine distance, map-based road distance and travel duration between pairs of locations.<\/p><\/div>\r\n        <div class=\"tr-card\"><h4>Add Time Window<\/h4><p>Apply a time window to a selected stop and observe how the operational constraint changes the route.<\/p><\/div>\r\n        <div class=\"tr-card\"><h4>Walking vs driving<\/h4><p>See where the engine recommends walking between nearby stops rather than moving the vehicle; walking legs are shown differently, including dotted segments.<\/p><\/div>\r\n        <div class=\"tr-card\"><h4>Walking Saving Time<\/h4><p>Estimate the time saved when the engine makes an efficient walk-versus-drive decision.<\/p><\/div>\r\n        <div class=\"tr-card\"><h4>Reorder route<\/h4><p>Change the sequence manually and see whether the modification improves or worsens route metrics and route shape.<\/p><\/div>\r\n        <div class=\"tr-card\"><h4>Export HTML<\/h4><p>Save a route visualisation for later review, side-by-side comparison or internal sharing.<\/p><\/div>\r\n      <\/div>\r\n      <h4 class=\"tr-accent-title\">Animate the route<\/h4>\r\n      <p>The Animate feature lets users watch the route progress from one stop to the next instead of viewing the complete sequence only as a static picture. This makes natural progression, unexpected jumps, backtracking and repeated visits to an area easier to recognise.<\/p>\r\n      <img decoding=\"async\" class=\"tr-image\" src=\"\/wp-content\/uploads\/trendroute-sandbox-guide-assets\/tr-sandbox-01-6f812648.jpg\" alt=\"TrendRoute route map with animation and solver comparison\">\r\n      <p class=\"tr-caption\">The route map supports visual inspection, solver switching and animation of the visit sequence.<\/p>\r\n      <div class=\"tr-footer\"><span>TrendRoute.ai | Sandbox Guide<\/span><span>8<\/span><\/div>\r\n    <\/section>\r\n\r\n    <section class=\"tr-page\">\r\n      <h2 class=\"tr-section-title\">3.1.4 Think You Can Beat the Optimiser? Try Manual Routing<\/h2>\r\n      <p>For users who want to interact with the routing problem directly, the Sandbox includes a manual-routing challenge. Instead of accepting an optimised sequence, the user selects the order in which the stops should be visited.<\/p>\r\n      <p>To keep the challenge engaging, the user has a maximum of two minutes to create the route. The interface tracks the remaining stops as the sequence is built.<\/p>\r\n      <div class=\"tr-box\">\r\n        <h4>The challenge<\/h4>\r\n        <p>Can you create a better route than the AI-powered TrendRoute V3 or TrendRoute V5 solution within two minutes?<\/p>\r\n      <\/div>\r\n      <p>Once the manual sequence is complete, the result can be compared with the optimiser. This is both an entertaining way to explore route planning and a practical demonstration of how quickly manual construction becomes difficult as the number of stops grows.<\/p>\r\n      <img decoding=\"async\" class=\"tr-image\" src=\"\/wp-content\/uploads\/trendroute-sandbox-guide-assets\/tr-sandbox-05-4aad60b8.jpg\" alt=\"Manual Routing challenge map\">\r\n      <p class=\"tr-caption\">Manual Routing challenge: select the stop sequence directly on the map while the time-limited challenge is running.<\/p>\r\n      <h4 class=\"tr-accent-title\">Reorder an existing route<\/h4>\r\n      <p>Manual experimentation is not limited to building a route from scratch. Users can also modify the sequence of an existing route and see whether the change reduces or increases distance, travel time, total duration and route-quality measures. It turns a dispatchers intuition into something that can be measured.<\/p>\r\n      <div class=\"tr-footer\"><span>TrendRoute.ai | Sandbox Guide<\/span><span>9<\/span><\/div>\r\n    <\/section>\r\n\r\n    <section class=\"tr-page\">\r\n      <h2 class=\"tr-section-title\">3.2 Last Mile - Multi Route Optimisation<\/h2>\r\n      <p>Single-route optimisation determines the best sequence for one vehicle. Multi-route optimisation introduces a larger challenge: how should all deliveries be divided between multiple vehicles, and how should each vehicles route then be optimised?<\/p>\r\n      <p>The engine must solve assignment and sequencing together. A strong solution should minimise unnecessary overlap between vehicles while creating geographically sensible and operationally balanced routes.<\/p>\r\n      <div class=\"tr-grid cols-2\">\r\n        <div class=\"tr-card\"><h4>Fleet configuration<\/h4><p>Test the number of vehicles, route limits and return-to-hub behaviour.<\/p><\/div>\r\n        <div class=\"tr-card\"><h4>Operational constraints<\/h4><p>Explore maximum distance, maximum duration, maximum\/minimum stops per route and service time.<\/p><\/div>\r\n        <div class=\"tr-card\"><h4>Visual fleet inspection<\/h4><p>Routes are displayed separately on the map using different colours, making allocation and overlap easy to inspect.<\/p><\/div>\r\n        <div class=\"tr-card\"><h4>Upload your own case<\/h4><p>Benchmark TrendRoute.ai on representative multi-route problems from your own operation.<\/p><\/div>\r\n      <\/div>\r\n      <p>Uploaded multi-route cases are subject to the same evaluation allowance of 3 uploaded cases per day and 50 per month.<\/p>\r\n      <img decoding=\"async\" class=\"tr-image\" src=\"\/wp-content\/uploads\/trendroute-sandbox-guide-assets\/tr-sandbox-06-872028b2.jpg\" alt=\"Multi-route optimisation fleet allocation and map\">\r\n      <p class=\"tr-caption\">Multi-route optimisation: fleet allocation, route constraints, comparison metrics and geographic route structure.<\/p>\r\n      <div class=\"tr-footer\"><span>TrendRoute.ai | Sandbox Guide<\/span><span>10<\/span><\/div>\r\n    <\/section>\r\n\r\n    <section class=\"tr-page\">\r\n      <h2 class=\"tr-section-title\">3.3 Shipment - Pickup &amp; Delivery<\/h2>\r\n      <p>Pickup-and-delivery routing introduces a precedence requirement: a shipment must be collected before it can be delivered. The optimiser therefore needs to find an efficient route while preserving the relationship between each pickup and its corresponding delivery.<\/p>\r\n      <p>This routing model is particularly relevant to express delivery, food delivery, on-demand transport, courier services and other collection-and-delivery operations.<\/p>\r\n      <div class=\"tr-box cyan\">\r\n        <h4>Example<\/h4>\r\n        <p>A courier may collect orders from several restaurants and deliver them to different customers. The route must remain efficient while every pickup is completed before its corresponding delivery.<\/p>\r\n      <\/div>\r\n      <p>The map visually distinguishes pickup and delivery locations, while the results expose familiar metrics such as distance, travel time, service time, total duration, stops per hour and route quality.<\/p>\r\n      <img decoding=\"async\" class=\"tr-image\" src=\"\/wp-content\/uploads\/trendroute-sandbox-guide-assets\/tr-sandbox-07-d93f5573.jpg\" alt=\"Pickup and Delivery route map\">\r\n      <p class=\"tr-caption\">Pickup &amp; Delivery mode: paired pickup\/delivery stops visualised on the route map.<\/p>\r\n      <div class=\"tr-footer\"><span>TrendRoute.ai | Sandbox Guide<\/span><span>11<\/span><\/div>\r\n    <\/section>\r\n\r\n    <section class=\"tr-page\">\r\n      <h2 class=\"tr-section-title\">3.4 Shipment - Multi-Step<\/h2>\r\n      <p>Some shipments require more than a pickup and final delivery. An item may need to pass through another location before reaching its destination.<\/p>\r\n      <div class=\"tr-box\">\r\n        <h4>Example<\/h4>\r\n        <p>An item is picked up at Location A, taken to Location B for validation, processing or an update, and then transported to its final destination at Location C.<\/p>\r\n      <\/div>\r\n      <p>Within the current Sandbox scenario, a shipment can include 0 or 1 intermediate step between pickup and final delivery. The general routing concept can be extended to support more intermediate steps for operations that require more complex flows.<\/p>\r\n      <p>The Sandbox distinguishes pickup, delivery, pickup &amp; delivery, and hub locations, and provides tools such as Show Timeline and Start Leg Navigator to help users understand the sequence and connection between shipment legs.<\/p>\r\n      <img decoding=\"async\" class=\"tr-image\" src=\"\/wp-content\/uploads\/trendroute-sandbox-guide-assets\/tr-sandbox-08-731e164f.jpg\" alt=\"Multi-Step shipment route map\">\r\n      <p class=\"tr-caption\">Multi-Step mode: visualise pickup, intermediate handling and final delivery within one coordinated routing problem.<\/p>\r\n      <div class=\"tr-footer\"><span>TrendRoute.ai | Sandbox Guide<\/span><span>12<\/span><\/div>\r\n    <\/section>\r\n\r\n    <section class=\"tr-page\">\r\n      <h2 class=\"tr-section-title\">3.5 Static Routes + Dynamic Parcels<\/h2>\r\n      <p>Many logistics operations start from static or recurring routes that already contain their normal deliveries. The challenge is what happens when new orders arrive after those routes have been planned.<\/p>\r\n      <p>Static Routes + Dynamic Parcels demonstrates how TrendRoute.ai can extend an existing plan rather than rebuilding everything from scratch.<\/p>\r\n      <div class=\"tr-grid cols-2\">\r\n        <div class=\"tr-card\"><h4>Start with existing routes<\/h4><p>The scenario begins with recurring\/static routes and their already assigned stops.<\/p><\/div>\r\n        <div class=\"tr-card\"><h4>Add dynamic orders<\/h4><p>Users can introduce new unassigned orders directly in the Sandbox.<\/p><\/div>\r\n        <div class=\"tr-card\"><h4>Insert where feasible<\/h4><p>The engine looks for a suitable nearby route with enough capacity and compatible constraints.<\/p><\/div>\r\n        <div class=\"tr-card\"><h4>Create a new route when needed<\/h4><p>If existing routes cannot absorb the remaining orders, a new route can be created for them.<\/p><\/div>\r\n      <\/div>\r\n      <h4 class=\"tr-accent-title\">Before and After comparison<\/h4>\r\n      <p>The results view makes the impact of route extension measurable by comparing distance, travel time, service time, total duration, number of stops and stops per hour before and after the dynamic orders are introduced. The interface also provides Extend and Rearrange controls for further experimentation.<\/p>\r\n      <img decoding=\"async\" class=\"tr-image\" src=\"\/wp-content\/uploads\/trendroute-sandbox-guide-assets\/tr-sandbox-09-48727514.jpg\" alt=\"Dynamic route extension before and after comparison\">\r\n      <p class=\"tr-caption\">Dynamic route extension: compare the existing plan with the extended plan after new parcels are introduced.<\/p>\r\n      <div class=\"tr-footer\"><span>TrendRoute.ai | Sandbox Guide<\/span><span>13<\/span><\/div>\r\n    <\/section>\r\n\r\n    <section class=\"tr-page\">\r\n      <h2 class=\"tr-section-title\">4. A Sandbox for Benchmarking - Not Just Demonstration<\/h2>\r\n      <p>The TrendRoute Sandbox was intentionally designed to be more than a polished product demo. Route optimisation is a difficult engineering problem, and realistic logistics operations involve much more than finding the shortest line through a collection of coordinates.<\/p>\r\n      <p>A strong routing engine may need to handle difficult geography, dense urban areas, large numbers of stops, multiple vehicles, time windows, pickup-before-delivery constraints, multi-step shipment dependencies, walking and driving decisions, recurring routes, dynamic orders, route-shape quality and different optimisation objectives.<\/p>\r\n      <div class=\"tr-box cyan\">\r\n        <h4>Our principle<\/h4>\r\n        <p>Route optimisation technology should be tested rather than simply described. The Sandbox gives users the tools to examine multiple approaches, inspect route shape, measure numerical differences, introduce constraints and challenge the optimiser themselves.<\/p>\r\n      <\/div>\r\n      <h4 class=\"tr-accent-title\">A practical benchmarking approach<\/h4>\r\n      <ul>\r\n        <li>Use the same routing problem and equivalent operational assumptions.<\/li>\r\n        <li>Compare distance, travel time and total duration.<\/li>\r\n        <li>Compare productivity through stops per hour.<\/li>\r\n        <li>Inspect route quality and geographical progression visually.<\/li>\r\n        <li>Check operational feasibility and walking decisions where relevant.<\/li>\r\n        <li>Upload a representative testcase when you want the comparison to reflect your own operation.<\/li>\r\n      <\/ul>\r\n      <h4 class=\"tr-accent-title\">Why we built it this way<\/h4>\r\n      <p>At TrendRoute.ai, we have built multiple optimisation capabilities because real logistics problems are diverse and often difficult. The best way to understand that capability is to challenge it with a realistic problem.<\/p>\r\n      <div class=\"tr-final-grid\">\r\n        <div class=\"tr-final-card\"><h4>Does the route only look good in the numbers?<\/h4><p>Or would a dispatcher actually use it in daily operations?<\/p><\/div>\r\n        <div class=\"tr-final-card\"><h4>Does it stay strong under constraints?<\/h4><p>Add time windows, route limits and operational rules and observe what changes.<\/p><\/div>\r\n        <div class=\"tr-final-card\"><h4>Can a human planner do better?<\/h4><p>Use Manual Routing or reorder the route and compare the result.<\/p><\/div>\r\n        <div class=\"tr-final-card\"><h4>How does it compare with recognised solvers?<\/h4><p>Run the same testcase across alternative methods and inspect the difference yourself.<\/p><\/div>\r\n      <\/div>\r\n      <div class=\"tr-cta\">TEST IT. COMPARE IT. CHALLENGE IT.<\/div>\r\n      <p class=\"tr-url\"><a href=\"https:\/\/trendroute.ai\/route-optimisation-sandbox\/\" target=\"_blank\" rel=\"noopener\">trendroute.ai\/route-optimisation-sandbox\/<\/a><\/p>\r\n      <div class=\"tr-footer\"><span>TrendRoute.ai | Sandbox Guide<\/span><span>14<\/span><\/div>\r\n    <\/section>\r\n\r\n  <\/div>\r\n<\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-4099492 e-flex e-con-boxed e-con e-parent\" data-id=\"4099492\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-eb550c4 elementor-widget elementor-widget-shortcode\" data-id=\"eb550c4\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-shortcode\">        <div id=\"tpgp-3853781\" class=\"tpgp-wrap\" data-pdf-id=\"4\" data-pdf-label=\"PDF 4\">\n            <button type=\"button\" class=\"tpgp-open\">Download PDF<\/button>\n\n            <div class=\"tpgp-modal\" aria-hidden=\"true\">\n                <div class=\"tpgp-backdrop\"><\/div>\n                <div class=\"tpgp-dialog\" role=\"dialog\" aria-modal=\"true\" aria-labelledby=\"tpgp-3853781-title\">\n                    <button type=\"button\" class=\"tpgp-close\" aria-label=\"Close\">&times;<\/button>\n                    <h3 id=\"tpgp-3853781-title\">Get the PDF<\/h3>\n                    <form class=\"tpgp-form\" novalidate>\n                        <input type=\"hidden\" name=\"action\" value=\"trendplus_gated_pdf_submit\">\n                        <input type=\"hidden\" name=\"nonce\" value=\"07de616405\">\n                        <input type=\"hidden\" name=\"pdf_id\" value=\"4\">\n                        <input type=\"hidden\" name=\"page_url\" value=\"https:\/\/trendroute.ai\/en\/wp-json\/wp\/v2\/pages\/944\">\n                        <div class=\"tpgp-hp\" aria-hidden=\"true\"><label>Website<input type=\"text\" name=\"website\" tabindex=\"-1\" autocomplete=\"off\"><\/label><\/div>\n\n                        <label>\n                            <span>Work email<\/span>\n                            <input type=\"email\" name=\"email\" autocomplete=\"email\" required>\n                        <\/label>\n\n                        <label>\n                            <span>Company name<\/span>\n                            <input type=\"text\" name=\"company\" autocomplete=\"organization\" required maxlength=\"190\">\n                        <\/label>\n\n                        <button type=\"submit\" class=\"tpgp-submit\">Download PDF<\/button>\n                        <p class=\"tpgp-privacy\">We\u2019ll use your details to provide the requested resource. 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TEST [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-944","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.6 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Sandboxguide: testa och j\u00e4mf\u00f6r ruttoptimering | TrendRoute<\/title>\n<meta name=\"description\" content=\"Kom ig\u00e5ng med TrendRoute Sandbox. 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