feat(algorithms): add SmsEmoa (S-Metric Selection EMOA)

Beume, Naujoks & Emmerich 2007: a steady-state MOEA that uses
hypervolume contribution as the secondary survival selection criterion.

Each generation:
- Generate ONE child via parent selection + variation + evaluation.
- Combine population + child, run non_dominated_sort.
- The discarded individual is the worst-front member with the
  smallest hypervolume contribution (computed via the new
  hypervolume_nd_from_evaluations helper).

Selection-quality is excellent at moderate objective counts (2–4) at
the cost of higher per-step compute (each survival selection requires
N+1 hypervolume evaluations of size ≤ N each). Best paired with a
tightly-bounded objective space — the user supplies a fixed reference
point in the config.

Tests: produces a non-empty front on Schaffer N.1, deterministic
reruns, panic on `population_size == 0`, panic on
`reference_point.len() != objectives.len()`.

src/prelude.rs

@@ -27,6 +27,7 @@ pub use crate::algorithms::{
     GeneticAlgorithm, GeneticAlgorithmConfig, HillClimber, HillClimberConfig, Ibea,
     IbeaConfig, Moead, MoeadConfig, Mopso, MopsoConfig, Nsga2, Nsga2Config, Nsga3, Nsga3Config, Paes, PaesConfig, ParticleSwarm,
     ParticleSwarmConfig, RandomSearch, RandomSearchConfig, SimulatedAnnealing,
-    SimulatedAnnealingConfig, Spea2, Spea2Config, TabuSearch, TabuSearchConfig, Umda,
+    SimulatedAnnealingConfig, SmsEmoa, SmsEmoaConfig, Spea2, Spea2Config, TabuSearch,
+    TabuSearchConfig, Umda,
     UmdaConfig,
 };