This repository contains all the code for the paper CRIO for Neighbourhood Change (Olson et al. 2020).
The conda environment file environment.yml at the base of the repository can be used to set up the exact environment we used for our experiments. This environment was used on Ubuntu 18.04, and may not be exactly replicable on other systems. If you have issues configuring the environment, try the alternate environment_simple.yml file.
Important: you must obtain a Gurobi license in order to run our code successfully. This can be obtained for free for academic purposes here.
Our experiments require the LTDB. Specifically, we used both Full and Sample datasets. Place these files, in .xslx format, into a folder named data at the root of the directory. Then, you can run notebooks/GenerateData.ipynb which will perform our pre-processing steps.
Our experiments are labelled by the model used, and can be found in the code folder. With the correct data in the data folder, they can be run from the command line as-is.