feat(traits,algorithms): add PartialProblem trait and Hyperband

Multi-fidelity optimization. Hyperband (Li et al. 2017) and its
foundation Successive Halving (Karnin et al. 2013) tune
hyperparameters by allocating *uneven* compute across configurations:
sample many cheap-to-evaluate-at-low-budget configs, then promote
the survivors to higher budgets. Crucial for ML hyperparameter
tuning where each evaluation is a partial training run.

This requires a new trait — `Problem::evaluate` is a single-shot
black box, but Hyperband needs to evaluate the SAME decision at
different fidelity budgets:

  pub trait PartialProblem {
      type Decision: Clone;
      fn objectives(&self) -> ObjectiveSpace;
      fn evaluate_at_budget(&self, decision: &Self::Decision,
                            budget: f64) -> Evaluation;
  }

`PartialProblem` is intentionally NOT a sub-trait of `Problem`.
Implementors who already have a `Problem` and want their
`evaluate_at_budget` to ignore budget can write a one-line wrapper.

`Hyperband` is the optimizer:

  pub struct HyperbandConfig {
      max_budget: f64, eta: f64, max_brackets: usize, seed: u64,
  }
  pub struct Hyperband<I> { config, initializer, ... }

Single-objective only. The decision sampler is an `Initializer<D>` so
it works the same way as every other heuropt algorithm. Generic over
decision type.

src/prelude.rs

@@ -6,7 +6,7 @@
 
 pub use crate::core::{
     Candidate, Direction, Evaluation, Objective, ObjectiveSpace, OptimizationResult,
-    Population, Problem, Rng, rng_from_seed,
+    PartialProblem, Population, Problem, Rng, rng_from_seed,
 };
 
 pub use crate::traits::{Initializer, Optimizer, Repair, Variation};
@@ -27,7 +27,8 @@ pub use crate::algorithms::{
     BayesianOptConfig, CmaEs, CmaEsConfig, DifferentialEvolution,
     DifferentialEvolutionConfig, EpsilonMoea, EpsilonMoeaConfig,
     GeneticAlgorithm, GeneticAlgorithmConfig, Grea, GreaConfig, HillClimber, HillClimberConfig, Hype,
-    HypeConfig, Ibea, IbeaConfig, IpopCmaEs, IpopCmaEsConfig, Knea, KneaConfig, Moead, MoeadConfig, Mopso, MopsoConfig,
+    HypeConfig, Hyperband, HyperbandConfig, Ibea, IbeaConfig, IpopCmaEs, IpopCmaEsConfig,
+    Knea, KneaConfig, Moead, MoeadConfig, Mopso, MopsoConfig,
     NelderMead, NelderMeadConfig, Nsga2,
     Nsga2Config, Nsga3, Nsga3Config, OnePlusOneEs, OnePlusOneEsConfig, Paes, PaesConfig, ParticleSwarm, PesaII, PesaIIConfig,
     ParticleSwarmConfig, RandomSearch, RandomSearchConfig, Rvea, RveaConfig,