feat(tsp): add binary ls, use 10k iterations instead of 5k

chore: update report

feat: add a lot of algorithm showcases

chore: part of report

chore(tsp): few minor updates

feat(lib): add evaluation count to EA stats

tests(tsp): move tests to proper modules, fix uses

feat(tsp): add MinimalSpanningTree initializer

feat(tsp): add 2opt perturbation for subsequence reversal

feat(tsp): add TSPInstance convertor to GenericGraph

feat(tsp): add minimal spanning tree and filter_edges

feat(tsp): add nearest neighbor initializer

feat(tsp): add cycle, no and partially mapped crossovers

refactor(tsp): split to multiple files out of tsp.rs

fix(lib): do not take mut self in population.iter()

feat(lib): add roulette wheel selection

refactor(tsp): put plotting to main to not repeat code

feat(lib): add random search

feat(tsp): add ea binary algorithm

tests(tsp): adapt to new binarystring -> node permutation implementation