Train optimizer

Hi!

Inspiration

The project seemed interesting and easy to start, but also deeply challenging.

What it does

It optimizes the waiting time for simulated passengers on a rail network.

How we built it

With python and various libraries for modelling, plotting and training.

Challenges we ran into

Modelling the railway components was a harder challenge than anticipated, as well as fitting them into an event driven loop in order to simulate trains and passengers moving in real time. Figuring out ways to visualize the data in 2D was definitely challenging, as well as learning and implementing new libraries such as seaborn and matplotlib.

Accomplishments that we're proud of

We think the code structure is much better than what we would've accomplished before. We're proud to have learned a lot in such a short time, and that we also had a lot of fun doing it, no matter the result.

What we learned

How to better structure code and model real life objects, how to communicate efficiently both online and offline, how to study and implement new libraries and tools.