lucasPDY / Machine-Learning-with-MiniZinc

Monash University Winter Vacation Research Project

Machine-Learning-with-MiniZinc

Monash University Winter Vacation Research Project The purpose of this repository is to showcase the capabilities of MiniZinc and showcase its integrations with different machine learning frameworks to solve satisfaction and optimization problems. This project was supervised by Dr. Guido Tack of Monash University.

There are two folders inside the repository:

1. Soda

   Using Machine Learning to predict the sales of different sodas and MiniZinc to optimize the amount of profit to be made using the estimated sales.

2. Taxi

   With a dataset of taxi rides around NYC, machine learning was used to predict the amount of time needed to travel from two different points in the NYC area. MiniZinc was used to solve a satisfaction problem involving minimizing the amount of time it takes for two taxis travelling several different locations.

For any questions, feel free to create an issue or PR.

Machine-Learning-with-MiniZinc was created by De Yuan Phang (Lucas Phang) and Lillie Esther as part of the Monash University Winter Vacation Research Project