This repository contains the code and documentation for a Vehicle Routing Problem (VRP) solution that was built for a blinds installation company in Australia. The client was having difficulties manually allocating, scheduling, and managing the routes of all its installers/employees. This project automated and optimized the Constrained Vehicle Routing Problem with Time Windows (CVRP-TW) to help reduce processing time and increase efficiency .
The main goal of this project was to automate and optimize the scheduling and route management for a blinds installation company in Australia. The company was having trouble manually managing the routes and schedules of all its installers/employees, which was leading to inefficiencies and increased processing time. This project is a tool that uses the concept of Constrained Vehicle Routing Problem with Time Windows (CVRP-TW) to solve the client's problem
To get a local copy up and running follow these simple steps.
- Install Anaconda, VS Code -
https://www.anaconda.com/download
https://visualstudio.microsoft.com/downloads/
- Open VS Code and install required libraries environment using conda
conda env create -f env39.yml
conda activate env39
- Now inside VS Code go to src directory and run main.py, passing a csv input file as an argument
python main.py ../data/processed_10.csv
- Create a Google Sheets App and make a 'Input' sheet and 'VRP Settings' with appropriate data schema.
- Create a Google Cloud function with the files in 'gcp-function'
- Now reate and run the Extension/Macro named 'VRP' in Google Sheets.
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated. If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks! :)
This project is licensed under the MIT license. For more information refer to the LICENSE.txt file.