Bachelor thesis - Implementing Job Reassignment Problem with Quantum Approximate Optimization Algorithm
Student: Adriano Lusso
Director: Christian Nelson Gimenez
Co-director: Alejandro Mata Ali
This repository has the complete implementation (algorithms, processes and experiments) for the my Computer Science bachelor thesis. The mail goal was to implement the Job Reassignment Problem (JRP) into the Quantum Approximate Optimization Algorithm (QAOA).
While the thesis is still in progress, the structure of the alredy done work will be explained on the following sections.
In this folder, you will find the first and most basic notebook, for start getting into the project. Here, i describe the components of the JRP, made it first QUBO implementation and run some basic tests over the QAOA.
Here, they are defined the classes and functions used for further more complex experiments. Inside this folder, an 'old' folder will also be available. Here, there some older versions of some functions that had been used in some of the first experiments. While they aren't deleted so as to keep that experiments working, it is recommended to just use the python files in the 'functions' directory.
This is just a duplicate of the OpenQAOA library repository. In some experiments, a local installation of the library will be done, so for that, the local repo is neccesary.
In the experiment with small instances, it has been discovered that a remote typical installation of OpenQAOA in Google Colab is not correctly done, due to dependencies prolem. This folder has some of the OpenQAOA files, but with the necessary modification needed for installing the tool on Google Colab.
An auxiliar experiment where i try a few small JRP instances with Google Colab + GPU.