i write an app like this about once a year (usually a java cmdline implementation). to my embarrassment, i never got it completely right. the last instalment e

i write an app like this about once a year (usually a java cmdline implementation). to my embarrassment, i never got it completely right. the last instalment even provided statistics that could be used to compare the effectiveness of different strategies and parameters. the last recent one featured: * classic genetic algorithm (population size etc) with different methods for selection and crossover * dumb hill climbing * the "additive" method described in OP's app * switching of methods at certain points (i.e. switch to hill climbing if the genetic algorithm didn't improve things for a certain time) * bitmap and svg output * statistics output that can be plotted with a plotting library so you can compare the effectiveness of different strategies * multithreading incl. tests to find out the sweet spot for the number of concurrent threads ~~~ i don't know why but i never really reached the point where my results were of a comparable quality to roger alsings mona lisa or even alteredQualia's image evolver (http://alteredqualia.com/visualization/evolve/ http://alteredqualia.com/visualization/evolve/). well, soon it's time for the next attempt. one interesting realisation: my desktop computer is about 10x as fast as the raspberry pi 3 for this kind of CPU intensive work.