feat(async): add run_async to every algorithm in the catalog

Async coverage was incomplete in 0.7 (only RandomSearch and
DifferentialEvolution had run_async). 0.8 closes the gap: every one
of the 33 algorithms now exposes
run_async(&problem, concurrency).await, gated on the async feature.

- Population-based algorithms fan out per-generation evaluations
  through evaluate_batch_async with concurrency-bounded
  FuturesOrdered chunks.
- Steady-state algorithms (HillClimber, SimulatedAnnealing,
  OnePlusOneEs, Paes, NelderMead) await each step sequentially;
  they accept the concurrency parameter for API uniformity.
- TabuSearch fans out the K-neighbor batch each step.
- Surrogate algorithms (BayesianOpt, Tpe) batch the initial design
  and await per-iteration acquisitions sequentially so the surrogate
  can update between picks.
- Hyperband uses a new AsyncPartialProblem trait (mirroring
  PartialProblem for multi-fidelity workloads) and a parallel
  evaluate_batch_at_budget_async helper; each Successive-Halving
  rung fans out its budgeted evaluations.

All paths preserve seeded determinism: RNG draws happen on the main
task in the same order as the sync path, and only the evaluations
are concurrent.

Adds a dedicated cookbook recipe at docs/book/src/cookbook/async.md
with a worked example (DifferentialEvolution under tokio) and
guidance on picking concurrency. Cross-references in SUMMARY.md
and cookbook.md are updated to surface the new recipe.

The follow-up docs commit reconciles the rest of the user guide
and README to describe the new feature; this commit is the bare
async surface.

docs/book/src/cookbook.md

@@ -7,8 +7,12 @@ project.
 ## Recipes
 
 - [Parallelize evaluation with rayon](./cookbook/parallel.md) — when
-  your `evaluate` is non-trivial, the `parallel` feature pays for
-  itself almost immediately.
+  your `evaluate` is non-trivial CPU work, the `parallel` feature
+  pays for itself almost immediately.
+- [Async evaluation](./cookbook/async.md) — when your `evaluate` is
+  IO-bound (HTTP / RPC / subprocess), the `async` feature lets the
+  optimizer await many evaluations concurrently. The differentiating
+  feature vs other optimization libraries.
 - [Tune a model with expensive evaluations](./cookbook/expensive-evaluations.md)
   — `BayesianOpt`, `Tpe`, and `Hyperband` for the 50–500-eval
   regime.