Some time in 2005 I started tinkering on working out a solver for impartial compact redistricting. There was one big false start around trying to use genetic algorithms that worked okay at zip-code level data but didn't scale up to the finest resolution Census data. Now I have two different algorithms implemented that seem to work pretty well. There was a phase of using a mesh triangulation package to fake up adjacency between census block centers, but eventually I downloaded the full geographic data with the lat,lon coordinate shapes of everything in the country and processed that to get real adjacency. I took all that geometric data and wrote my own rasterizer because other packages seemed cumbersome and inefficient when dealing with 600,000 polygons of 4-20 edges each. There was a bug in that rasterizer that went unsolved for about six years. I wrote what could have been used as a distributed client, but I only ever ran it on one computer and that turned out to be enough. I had scripts collecting the best solutions I found and had a bug in which one they presented that went undetected for around five years. I got a few shout outs from minor tech bloggers and one article in a law journal. In 2014 I got cited by a washington post blogger declaring, "This Computer Programmer Solved Gerrymandering In His Spare Time". And most recently I got invited to speak at TEDx Cambridge where I gave a ten minute talk on gerrymandering in the US and an impartial alternative.
I'm not sure what's next, but there are a few things to try before 2020.