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The LC Routing Project is a #web-based tool that analyzes and #optimizes waste collection routes using uploaded CSV data for stops and landfill sites. It provides route comparison, detailed segment data, and supports #DRT to #SWG conversion.

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aimaster-dev/lc-routing-optimization-backend

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♻️ LC Routing Project

The LC Routing Project is a web-based tool designed to analyze, compare, and optimize logistics routes for landfill and haul operations. Users can upload CSV files containing stop data and landfill information, visualize routes, and generate optimized paths for improved efficiency in waste collection and transportation.


🚀 Features

  • Upload and analyze CSV files for stops and landfill sites
  • Visual route selection interface for user-friendly interaction
  • Route optimization at the click of a button
  • Compare actual and optimized routes side-by-side
  • Detailed breakdown of each route segment
  • DRT to SWG conversion toggle available

📂 Input Data

The app requires two CSV files:

  1. Stops Array CSV – Contains a list of route stops to be analyzed
  2. Haul and Landfill CSV – Contains landfill and haul site information

These files should come from a prior data transformation process.


🧭 How to Use

  1. Open the web interface by navigating to the service URL.
  2. Upload the Stops Array CSV and Landfill CSV files.
  3. After a successful upload, select a route from the interface.
  4. Click "Optimize Route" to generate a new optimized route.
  5. Use "Compare Routes" to view differences between actual and optimized paths.
  6. Scroll down to view detailed segment information.
  7. If supported, toggle DRT to SWG conversion as needed.

📖 Reference

For a detailed breakdown of the methodology used in route optimization, see the companion Medium article: 👉 Optimizing Large Container Routes with GIS, Gurobi, and Python – A Real World Guide (Part 1: CSV)


🛠 Future Improvements

  • Export of optimized routes
  • Integration with mapping APIs (e.g., Google Maps, Mapbox)
  • Mobile support for field use
  • Advanced analytics on route efficiency and cost savings

📜 License

This project is licensed under the MIT License. See LICENSE file for more information.


🤝 Acknowledgments

Special thanks to the data transformation and logistics teams involved in preparing the input datasets for the routing process.


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