Solving Vehicle Routing Problems with Time Windows using multiple Classic Heuristic and metaheuristic algorithms (Hybrid Genetic Search (HGS), Guided Local Search (GLS), Ant Colony Optimization (ACO), Simulated Annealing (SA)), then comparing results with each one's results and present it in the graph. This was my master's thesis project.

Vehicle Routing Problems with Time Window (VRPTW), Hybrid Genetic Search (HGS), Guided Local Search (GLS), Ant Colony Optimization (ACO), Simulated Annealing (SA), MACS-VRPTW, Genetic Algorithm (GA), Exact, Heuristics, Metaheuristics, Machine Learning Algorithms, GRASP, Local Search (LS), Neighborhood Search, OR-Tools, VRP, VRPTW, Vehicle Routing Problems (VRP), pyVRP.

Using the Python Jupyter Notebook is highly advised. While compiling, each model executes independently. However, if you run the code straight from main.py , the application may crash and display errors due to the ACO procedure’s use of multiple threads! However, it functions perfectly now that I’m using the Python Jupyter Notebook code.

To have a thorough understanding (about the parameter tuning and machanise) of my Vehicle Routing Problem with Time Windows project, I recommend reading my master's thesis. Thank you.

python -m venv .venv

. .venv/bin/activate

pip install -r requirements.txt

git clone {paste repository URL}