This repository contains variety of examples of math programming models implemented primarily with
the Python Optimization Modeling Objects package and written into Jupyter notebooks.
A few examples also compare and contrast pyomo-based development with gurobipy-based development.
I am an active member of the INFORMS student chapter at the University of Texas at Austin. In that capacity, I have so far led two tutorials using examples from this repository. Recordings of those tutorials are hosted on YouTube at the links below.
Python has taken the data science world by storm but sometimes understanding what all packages and which versions are required to run a piece of code can be frustrating. Thankfully, we have companies like Anaconda, Inc. (headquartered in downtown Austin, TX!) making software versioning easy with tools like Anaconda. I have built and tested a conda environment using Anaconda 4.10.1 and exported it to this yaml file. The Anaconda environment may be built from file and activated as follows.
conda env create --file environment.yaml
conda activate pyomo-tutorials
I have only tested this on Fedora 34 with x86_64 architecture. I do not guarantee that this environment will work across all operating systems and architectures, but it should at the very least serve as a basis of support to get these codes working on your system.