# Optimal Tour Planning - Jupyter Notebooks

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

#### Notebook 5.1 - Travelling Salesman Problem - MTZ Formulation

This notebook gives an overview of solving the travelling salesman problem using the Miller-Tucker-Zemlin (MTZ) formulation. We will be back to using `PuLP`

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#### Notebook 5.2 - Travelling Salesman Problem - Brenchmarking the MTZ model

The solution time for MTZ models of different problem sizes increase drastically. So, in this notebook, we learn to benchmark the performance of the MTZ model for varying problem sizes.

#### Notebook 5.3 - Travelling Salesman Problem - Nearest Neighbour Heuristic

Using the nearest neighbour method learned in class, we learn to solve the travelling salesperson problem.

#### Notebook 5.4 - Travelling Salesman Problem - Genetic Algorithm

We solve the travelling salesperson problem using genetic algorithm (GA).

#### Notebook 5.5 - Travelling Salesman Problem - Solution Comparison

We compare different methods of solving the travelling salesperson problem.

#### Notebook 5.6 - Multiple Travelling Salesman Problem

In this notebook, we explore the travelling 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: