This was a project made for my JMU CS412 class which involved choosing a known NP-Complete problem in programming, researching exact solution algorithms, researching efficient and effective approximation algorithms, and then writing programs to indicate the approximation effectiveness as well as a presentation to discuss the problem.
For the implementation of the approaches I used Python, with NetworkX and Matplotlib being used for visualizations of the graphs. These implementations were done to fit pseudocode presented in the respectively cited papers which can be found in the works cited slides of the presentations.
This project assisted greatly in helping me handle scientific research specifically within the field of computer science. While I'd had experience with this form of research in other fields prior, this project was the first where I would have to dive headfirst into the abstractions and jargon of computer science researchers. This skill of reading professional documentation and researching more official sources is always a great one to have in a field so dependent on new information.
This project is public on GitHub with the direct approval of my JMU CS412 professor Dr. Zhuojun Duan.