# Optimal Tour Planning - Jupyter Notebooks

In the following notebooks, we learn to solve the traveling salesman problem (TSP) using different algorithms.

**Travelling Salesman Problem - MTZ Formulation**: This notebook gives an overview of solving the traveling salesman problem using the Miller-Tucker-Zemlin (MTZ) formulation. We will be back to using`PuLP`

.**Travelling Salesman Problem - Benchmarking the MTZ model**: The solution time for MTZ models of different problem sizes increases drastically. So, in this notebook, we learn to benchmark the performance of the MTZ model for varying problem sizes.**Travelling Salesman Problem - Nearest Neighbour Heuristic**: Using the nearest neighbor method learned in class, we learn to solve the traveling salesperson problem.**Travelling Salesman Problem - Genetic Algorithm**: We solve the traveling salesperson problem using a genetic algorithm (GA).**Travelling Salesman Problem - Solution Comparison**: We compare different methods of solving the traveling salesperson problem.**Multiple Travelling Salesman Problem**: In this notebook, we explore the traveling salesperson problem with multiple salespeople.

### Running the notebooks

You can download a zip file containing all the notebooks that we covered in this session from the link below: