Z-ENG: Assistance System for Logistics: Route Optimization

Félév: 2025-2026 ősz

Kategória: Szoftver

Téma leírása

This project aims to develop a demonstration prototype of a logistics assistance system for intercity transportation. Such system could support logistics companies in selecting optimal routes by considering distance, estimated travel time, vehicle load, and – optionally – real-time traffic conditions. As a core functionality, the prototype should integrate free routing APIs with a web-based visualization tool, allowing users to compare alternative routes and make informed decisions. As an extension, a machine learning module may be included to predict potential delays and adjust route recommendations dynamically. This will serve as a proof of concept for how AI methods can improve logistics operations, even with open-source tools and limited data.

Target Audience

• Logistics companies and delivery services
• Route and transportation managers

Mandatory tasks:

1. Optimal route calculation based on distance and estimated time
2. Route visualization: interactive maps via OpenStreetMap + Leaflet.js
3. API integration with a free routing service (e.g., GraphHopper or OSRM)

Optional tasks (Extension):

1. Arrival time and delay prediction using a simple machine learning model trained on open or synthetic traffic data
2. Dynamic adjustment of route recommendations based on ML predictions

Technologies (the student is encouraged to reconsider this list):

• Backend: Python (open source)
• Machine Learning (optional): TensorFlow or PyTorch
• Maps & Routing: OpenStreetMap + Leaflet.js, GraphHopper/OSRM API
• Frontend: Web interface (HTML/JS + Flask)
• Deployment: Local server or free cloud hosting (Render, Railway, Heroku free tier)

 
Optimization Focus

• Mandatory: Delivery time (primary metric)
• Optional: Fuel/energy consumption and transportation costs as future extensions

Feltételek

• Interest towards the topic, good command of English

Maximális létszám: 1 fő