MILP Problem Solver

This project aimed to determine an optimal selection of areas/polygons from a given dataset based on adjacency and cost constraints. I understand this solution is incomplete; however, I am willing to

Setup

This setup assumes that the current computer is on Windows.

1. Download and install Anaconda from the official Anaconda website.

2. Clone this repository in your choice of folder.

3. Open an Anaconda Prompt or Anaconda PowerShell Prompt in your cloned repo and run the following commands to install the necessary libraries. Agree to each prompt which prompted.

   conda env create -f environment.yml

4. Run the following command to set up the environment in Jupyter Notebook:

   python -m ipykernel install --user --name=testenv

5. Download GPLK for Windows from this link, and copy the glpk-#.### folder into C:\.

6. Open the Jupyter Notebook file, and select the kernel to be "testenv". You are now free to run the Jupyter Notebook code blocks.

Credits / References

Much of my work would not have been possible were it not for the following resources and many others:

• https://stackoverflow.com/questions/32316069/pyomo-cant-locate-glpk-solver
• https://www.datacamp.com/tutorial/pyomo
• https://bobbyhadz.com/blog/conda-create-and-install-requirements-txt
• https://stackoverflow.com/questions/70594482/pyomo-selecting-a-subset-of-domain-values-to-create-an-optimal-set