This project implements a genetic algorithm to optimize flight schedules and ticket costs for a group of researchers traveling to a conference in Rome. The goal is to minimize the total waiting time at the airport and the cost of airfares.
- Schedule Optimization: Ensures that the arrival and departure times of flights are aligned to minimize waiting times.
- Cost Minimization: Searches for the most economical flight options, considering time restrictions.
- Multiple Test Simulations: Performs multiple tests to ensure the robustness and efficiency of the algorithm.
- Python 3.8 or higher
- Additional Python libraries such as numpy and matplotlib for execution and visualization of results.
- Clone the repository:
git clone https://github.com/ThaisBarrosAlvim/GeneticAlgorithm - Install the dependencies:
pip install -r requirements.txt - Run the main script:
python main.py
The evolution of fitness over generations can be viewed in the following graph:
Distributed under the MIT License. See LICENSE for more information.