ICFP Contest 2023

Team: AStormOfMinds

Members:

• Christoph Breitkopf (Hannover, Germany)
• Jan Dreske (Vienna, Austria)

Tools

We used Python for experimentation, exploration, and visualization, and Rust for our actual solver.

Solution approach

• Place musicians in a regular rectangular grid on the whole stage.
• Optimize placement using simulated annealing. New placements are generated randomly using the following operations:
  • Swapping the positions of two musicians
  • Moving a musician
  • Changing the volume of one musician

We did not do well this year, scoring only about half of the top 10 scores, and probably ended up somewhere from place 65-80.

Problems encountered / Lessons learned

• Bugs in our (incremental) score computation consumed much time
• Some trivial tasks, like the initial placement in a grid, took way too much time
• Our optimization converges too slowly and requires much code tuning to get a result. We should have investigated other approaches with faster convergence.
• We would have needed incremental score computation and a faster line-of-sound algorithm for better performance. We looked at a scan-line approach for the latter but failed to see how to adapt that to the problem.
• We should have spent more time solving problems by hand or improving computed solutions manually. That would have required writing an interactive visual solver tool, though, for which we lacked time.
• A live visualization during the optimization would likely have been very helpful to see if the optimization converges and give hints for parameter tuning.

Overall

Fun problem and short and readable task specification.

• Suitable for both one-person and larger teams
• The website and REST API were very helpful
• The contest was a lot of fun. Big thanks to the organizers!