Supply Chains - Jupyter Notebooks
This notebook gives an overview of solving the continuous facility problem using the
cvxpy python-embedded modeling language for convex optimisation problems. We cannot use the default solver provided by
PuLP, as we are working with non-linearities.
This notebook gives an example of how to solve a single facility network location problem using
This notebook extends on the single facility network location problem through introduction of a new variable, the number of facilities.
To solve the capacitated facility network location problem, we first generate random facility capacities and customer demands and continue with
In this notebook, we estimate the level of service for a given facility capacity of a set number of facilities.
We encourage you to have a look at the notebooks and understand the differences between the various supply chain problems.
You can download all notebooks for Session 5 along with the data used in the notebook 5.1 from the link below.