Tutorial Background Information
For organisations delivering humanitarian aid to communities in need at times of crisis, it is imperative that the organisations finite resources are utilised to the optimal effect. Whether the aid is medical, food assistance, shelter or anything else, an optimal set of facility locations is imperative in order to maximise the impact of the group's financial and human resources.Â
In this tutorial you will learn how to frame and solve this facility location optimisation problem using genetic algorithms. Such problems usually crop up in business strategy or supply chain management settings, so this tutorial also demonstrates that problems which have been solved in a for-profit setting can often be reapplied to the benefit of non-profit organisations.
Prerequisite Knowledge for the Tutorial
The coder's version of the tutorial below assumes you know how to code using Python. Genetic algorithms are used, but are explained during the tutorial. However, if you would like to read a little about the basics of genetic algorithms, this GeeksforGeeks page explains the concept concisely.
If you don't know how to code in Python, don't worry, the non-coder's version doesn't require you to write any code. Also, there is a Python coding page on this website with a list of resources to help you learn to code if you would like to learn and do the coder's version of the tutorial later.
The Tutorial
These buttons will open a Google Colab notebook which constitutes the tutorial: