feat(algorithms): add EpsilonMoea (ε-dominance MOEA, Deb et al. 2003)

Replaces strict Pareto dominance with ε-dominance: A ε-dominates B when
`floor(A_i / ε) ≤ floor(B_i / ε)` for every objective and strictly
less in at least one (minimization frame). The result is a regular
discretization of objective space — at most one archive member per
ε-box — so the front spreads out automatically and the archive size
self-limits without truncation tricks.

Steady-state design: each generation samples one parent from the main
population and one from the ε-archive, applies variation, evaluates
the child, and offers it to both archives. Every member's
ε-coordinates and the box-tie rules are precomputed each insertion.

Tests: produces a front on Schaffer N.1 with reasonable spread,
deterministic reruns, panic on `epsilon[i] <= 0.0` and on
`epsilon.len() != objectives.len()`.

src/prelude.rs

@@ -23,7 +23,7 @@ pub use crate::operators::{
 
 pub use crate::algorithms::{
     AntColonyTsp, AntColonyTspConfig, CmaEs, CmaEsConfig, DifferentialEvolution,
-    DifferentialEvolutionConfig,
+    DifferentialEvolutionConfig, EpsilonMoea, EpsilonMoeaConfig,
     GeneticAlgorithm, GeneticAlgorithmConfig, HillClimber, HillClimberConfig, Hype,
     HypeConfig, Ibea, IbeaConfig, Moead, MoeadConfig, Mopso, MopsoConfig, Nsga2,
     Nsga2Config, Nsga3, Nsga3Config, Paes, PaesConfig, ParticleSwarm, PesaII, PesaIIConfig,