In this first post I want to share with you guys a piece of code I wrote to "solve" a problem where geometry meets optimization. I say "solve" because I didn't actually do anything that fantastic regarding the actual problem I address, but rather developed a small tool to help visualize the geometrical part of the problem. Even so, I do believe that for the smaller cases my tool can solve the problem.
The problem is along the lines of: define an energy function whose value depends on the positions of points in a sphere, and now try to minimize/maximize it (depending on a parameter). That is it. I used my coding skills to write an algorithm that solves this when the number of points is small, and that lets me see the creation of the solution: I create a random distribution of points and then let them adjust themselves to their desired positions, hopefully reaching the desired minimum/maximum.
In here you can find the report I wrote for this, in English. The code, some figures and some animations (GIFs like the one up there) can be found here.
Get ready for 12 intense days of problem-solving. The “Algorithm Mastery Bootcamp” starts December 1st and it will feature 24 programming challenges, live analysis sessions, a supportive community of like-minded problem-solvers, and more! Join now and become the Python expert others can rely on.