This program is part of a project I worked on in my role as a strategy & investment analyst at a public infrastructure agency. I developed the program and underlying algorithm as a way to provide the team with more actionable metric for identifying inefficient use of space within the portfolio.
In summary, it consists of a discrete optimisation program which models the ideal combination of buildings at each site, according to the estimated utilisation of each building. The selection and allocation of parameters is highly flexible, allowing users to model outcomes under a variety of scenarios.
Two aspects of this project made it particularly enjoyable: it served as an excellent introduction to object-oriented programming, and it was also rewarding to create a transformation pipeline that synthesises data from 5 data sources into a single metric.