feat(algorithms): add NSGA-II

Standard (μ+λ) NSGA-II with binary tournament parent selection on
(rank, crowding distance) and elitist survival selection on the combined
parent + offspring population (spec §12.3):

1. Initialize population_size random decisions.
2. Each generation: select parents by binary tournament (rank ↑ then
   crowding ↓ then random), apply variation, evaluate offspring,
   combine, non_dominated_sort, fill the next population front-by-front
   trimming the partial last front by crowding distance descending.
3. Return final population, Pareto front, best (None for >1 objective),
   evaluation count, and generation count.

Internal Nsga2Entry { candidate, rank, crowding_distance } stays
private. Panics with clear messages on `population_size == 0` or
empty `vary` output. Tests cover population length, evaluation count,
non-empty front, and full determinism with the same seed (spec §18.4).

src/algorithms/mod.rs

@@ -1,7 +1,9 @@
 //! Built-in reference optimizers.
 
+pub mod nsga2;
 pub mod paes;
 pub mod random_search;
 
+pub use nsga2::*;
 pub use paes::*;
 pub use random_search::*;