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/prelude.rs

@@ -18,4 +18,6 @@ pub use crate::pareto::{
 
 pub use crate::operators::{BitFlipMutation, GaussianMutation, RealBounds, SwapMutation};
 
-pub use crate::algorithms::{Paes, PaesConfig, RandomSearch, RandomSearchConfig};
+pub use crate::algorithms::{
+    Nsga2, Nsga2Config, Paes, PaesConfig, RandomSearch, RandomSearchConfig,
+};