A Python-based implementation of an optimization algorithm for delivery route planning, inspired by the Traveling Salesman Problem, accounting for traffic variations and leveraging advanced algorithmic concepts.
This project is a Python implementation of an optimization algorithm designed to solve a delivery route planning problem, inspired by the Traveling Salesman Problem (TSP). The algorithm aims to calculate the most optimal delivery route on a road network, connecting a subset of cities and returning to the starting point while minimizing the total travel time. The solution accounts for traffic variations during different time slots, enhancing its practicality for real-world applications. The implementation was developed in Python using Jupyter Notebook, leveraging concepts from Operational Research and advanced algorithmic complexity.
This project was undertaken during my first year of engineering studies (Bac+3 in the French education system) as part of a school assignment, providing valuable hands-on experience in algorithm design, problem-solving, and collaboration within a team of three.
To install and run the Advanced Algorithmic script, follow these steps:
- Clone the repository:
git clone https://github.com/Victor-Pavageau/AdvancedAlgorithmic.git- Navigate to the project directory:
cd AdvancedAlgorithmic-
Install the required dependencies:
Make sure you have Python installed.
To run the script, you can open the .ipynb file in Visual Studio Code or Google Colab.
Development: The development of this project was completed in June 2022.
Maintenance: This project is no longer maintained.
Future updates: No future updates are planned for this project.