Freight Distribution - Jupyter Notebooks
In the following notebooks, we learn to solve the travelling salesman problem (TSP) and vehicle routing problem (VRP) using different algorithms.
This notebook gives an overview of solving the travelling salesman problem using the Miller-Tucker-Zemlin (MTZ) formulation. We will be back to using
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.
Using the nearest neighbour method learned in class, we learn to solve the travelling salesperson problem.
We solve the travelling salesperson problem using genetic algorithm (GA).
We compare different methods of solving the travelling salesperson problem.
In this notebook, we explore the travelling salesperson problem with multiple salespeople.
We solve the capacitated vehicle routing problem to improve on the solution of the multiple travelling salesperson problem.
To solve the vehicle routing problem quickly, perhaps even at the cost of not having the best solution, we apply the sweep method, as learned in class.
We solve the vehicle routing problem, we apply the savings method, as learned in class.
We again apply the genetic algorithm, but this time to solve the vehicle routing problem.
We encourage you to have a look at the notebooks and understand the differences between the various algorithms to solve the travelling salesperson problem and the vehicle routing problem.
You can download all notebooks for Session 6 along with the data used in the notebook 6.3 from the link below.