arnobt78 / vrptw-solver-comparison

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

vrptw-solver-comparison

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

keywords

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.

Important Note

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.

More Details

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.

Development

Create venv

python -m venv .venv

Activate venv

. .venv/bin/activate

Install requirements

pip install -r requirements.txt

Clone git repository URL

git clone {paste repository URL}