Development of logistics and routing system (web + mobile application)

Budget: 150000 UAH Deadline: 80 days

Good day.

I can implement such a system with a web cabinet for the logistics manager and a mobile application for drivers.

For the tech stack, I propose:

web: React / Next.js / TypeScript / Tailwind
mobile: React Native
backend: Node.js / NestJS
database: PostgreSQL
realtime: WebSocket / Socket.IO
maps / routing: Google Maps API, OpenStreetMap, OSRM

I plan to implement routing through a separate optimization module:

building routes based on a set of points and several vehicles
optimization based on distance, time, load, and specified constraints
consideration of time windows, limits on points, geography, and transport capacity
identification of points that do not fall into the route, with documentation of reasons
the ability to recalculate routes when statuses or conditions change

In the web part, I will implement:

creation and editing of routes
automatic route building
execution control
monitoring of vehicles and statuses
history and analytics

In the mobile application for the driver:

receiving the route
list of points
navigation
marking completed deliveries
updating status and geolocation in real-time

Examples of recent works:

Alytic - https://www.alytic.sa/
Tornix - https://www.tornix.ai/
LeagueIT - https://www.leagueit.org/

Estimated assessment:

MVP: from 10 weeks
budget: from 4000 USD

The exact estimate depends on the number of vehicles, points, types of constraints, logic of route rescheduling, and analytics requirements.

I am ready to discuss the details and propose a phased implementation plan. Expand

Budget: 120000 UAH Deadline: 75 days

Hello! The development of a VRP (Vehicle Routing Problem) system is a challenge that requires not only a quality interface but also a powerful mathematical core. I specialize in automating complex logistics processes and developing high-load systems using mapping services. My approach is based on creating a fault-tolerant architecture where the optimization algorithm works in tandem with real-time monitoring, ensuring fuel and time savings of 20-30%.

🛠 Technology Stack
* Backend (Core): Python (FastAPI) — ideal for mathematical computations and fast API performance.
* Routing: OSRM (for quick graph construction) + Google OR-Tools (the best library for solving VRP/TSP problems with constraints).
* Maps & Geocoding: Leaflet / OpenStreetMap (for budget savings) or Google Maps API (for maximum accuracy of traffic).
* Frontend (Logistics): React / Next.js with interactive maps and dashboards.
* Mobile (Driver): Flutter (one code for Android and iOS) with background geolocation tracking.
* Database: PostgreSQL + PostGIS (geospatial extensions for working with coordinates).

🧠 How I plan to implement routing (VRP)
* Distance Matrix: Building a real-time matrix of time and distances between all points using OSRM or GraphHopper.
* Optimization Algorithm: Using Google OR-Tools to account for your constraints:
* Capacity Constraints: vehicle load capacity.
* Time Windows: delivery time windows.
* Resource Constraints: limit of points per driver.
* Handling "unassigned" points: The algorithm automatically discards nodes that do not fit within the limits and outputs them to the logistics manager in a separate "Unassigned" list for manual reassignment or relocation.

📂 Experience in similar tasks
I have experience in developing monitoring and automation systems for courier services, where I implemented algorithms for distributing orders among the nearest couriers considering the queue. (Detailed examples of architecture and screenshots of modules will be sent in personal messages).

⏱ Approximate estimate (MVP version)
Since the project is large-scale, I propose a phased development:
* Stage 1: Web panel + Routing core (VRP): 25–35 working days.
* Stage 2: Mobile application for drivers: 20–25 working days.
* Stage 3: Online monitoring and analytics: 10–15 working days.
Cost (adjusted to the Ukrainian market):
* Development of the entire system (MVP): 120,000 – 180,000 UAH.
* Support and scaling: discussed separately.

Why me:
As an automation specialist, I will configure the system to learn on its own. Expand

Budget: 100000 UAH Deadline: 10 days

Good day. I am ready to complete this project as I have extensive experience in application development.

Budget: 3000 UAH Deadline: 21 days

Hello!

We have experience in developing systems with logistics, routing, and real-time monitoring. To solve the VRP problem, we plan to use OSRM or Google Maps Directions API in combination with optimization algorithms from Google OR-Tools, which allows for effective distribution of points among vehicles considering time windows, load constraints, and geography.

Stack: Laravel + Vue.js for the logistics web interface, React Native for the driver mobile application, WebSockets for real-time status updates and geolocation. The architecture is designed for scalability to accommodate growth in the number of points and vehicles without rewriting the core of the system.

Please write in private messages, and I will provide examples of relevant projects, exact costs, and timelines for implementation by stages.

Best regards, Mykola

Budget: 1200 UAH Deadline: 1 day

Good day
I have completed identical tasks and can demonstrate the result (except for online monitoring, it all depends on the tracker or the service you want to use).
If relevant, feel free to write, I would be happy to work with you.

Budget: 100000 UAH Deadline: 30 days

Hello, Mykola!

I am ready to implement a logistics system with automatic routing according to your requirements — with a web part for the logistics manager and a mobile application for drivers.

From my side, I will establish an architecture that withstands scaling: a backend for route calculations, a separate service for optimization (VRP), a database with route history and statuses, a web interface for management, and a mobile application for execution.

Regarding routing: I will use VRP algorithms considering your constraints (time, load, number of points, geography). As a base — OSRM/Google Maps for distances and time, then an optimization layer (for example, OR-Tools) that distributes points among vehicles, builds routes, and shows problem points that do not fit.

I will create the web part as a dashboard: route creation, auto-generation, execution control, analytics. The mobile application will be simple and stable: route, list of points, statuses, real-time updates.

Regarding the stack:
backend — Python (FastAPI) or Node.js
optimization — Google OR-Tools
maps — Google Maps API or OpenStreetMap + OSRM
frontend — React
mobile — React Native

I suggest breaking the work into stages: first MVP (core routing + basic interfaces), then expanding functionality and optimization based on real data.

Implementation time: 30 days
Cost: $2500

I have a couple of questions:
What is the approximate number of points and vehicles on average per route?
Is integration with your current systems (CRM/ERP) needed in the first stage?

After the first stage, I will add a bonus: I will prepare recommendations for route optimization based on your data to reduce costs and increase delivery efficiency.

I look forward to collaborating! Expand

Budget: 100000 UAH Deadline: 30 days

Hello!

This is a serious engineering task (Vehicle Routing Problem), with which I have practical experience. Many developers try to solve it "head-on" (by simply sorting by the nearest point), which leads to terrible routes. I use professional mathematical solvers for multi-factor optimization.

I will answer your questions point by point:

1. How I plan to implement routing (Core Architecture): A two-step approach is needed here so that the system works quickly and does not "eat" thousands of dollars on the Google Maps API:

- Distance Matrix Generation: I will deploy my own OSRM (Open Source Routing Machine) engine on your server or use OpenRouteService. This will allow calculating time and distance between hundreds of points for free and in milliseconds (Distance Matrix).
- Optimization (VRP/TSP): I will use the Google OR-Tools library. It perfectly solves CVRP (capacity constraints of vehicles) and VRPTW (time window constraints of customers). The algorithm will automatically "discard" points that are physically impossible to visit and distribute the rest among the available fleet.
2. Technology stack:

- Backend: Python (FastAPI). Python is the only right choice here, as it has the best integration with OR-Tools and libraries for working with geodata.
- Database: PostgreSQL with PostGIS extension (for fast searching by coordinates and geo-zones). Redis + WebSockets for real-time vehicle tracking.
- Frontend (Web for the logistician): React.js + TailwindCSS + Leaflet/Mapbox for interactive work with the map.
- Mobile application (Driver): React Native (Expo). One codebase for both iOS and Android. For navigation — deep links to installed Waze/Google Maps on the phone.
3. Experience with similar projects: I developed a logistics core for a delivery service (water/groceries). Implemented: dynamic route recalculation (if the driver is late), automatic distribution of 300+ orders to 10-15 couriers considering trunk volume, as well as live tracking of couriers on the map for the dispatcher.

4. Cost and timeline estimation: Thanks to the availability of ready-made developments on the OR-Tools architecture and the use of cross-platform frameworks, I can deliver a finished product 2-3 times faster than standard teams.

- Stage 1 (Routing Core + Basic API): 7–10 days.
- Stage 2 (Logistician Web Panel with Map): 10–14 days.
- Stage 3 (Driver Mobile Application + Live Tracking): 10–14 days.
- Total timeline for a full MVP: 1 - 1.5 months.
- Estimated budget: $2500–4000 (depends on the number of screens). Expand