Replace the internal Vec<CompletedTrial<V>> with a pluggable Storage<V>
trait. MemoryStorage is the default (no behavior change for existing
users). Behind the `journal` feature flag, JournalStorage persists
trials to a JSONL file with fs2 file locking for multi-process safety.
- Storage<V> trait with push(), trials_arc(), refresh() methods
- MemoryStorage<V> wraps Arc<RwLock<Vec<CompletedTrial<V>>>>
- JournalStorage<V> appends JSON lines with exclusive file locks
- Study::with_sampler_and_storage() general constructor
- Study::with_journal() convenience constructor (journal feature)
- Refresh from storage on create_trial() for multi-process discovery
- MSRV bumped to 1.89
Add MultiObjectiveStudy for optimizing multiple objectives simultaneously,
backed by NSGA-II (Non-dominated Sorting Genetic Algorithm II) with SBX
crossover, polynomial mutation, and constraint-aware dominance.
New public API:
- MultiObjectiveStudy with optimize(), pareto_front(), ask()/tell()
- MultiObjectiveTrial with get(), is_feasible(), user attributes
- MultiObjectiveSampler trait for custom MO samplers
- Nsga2Sampler with builder for population size, crossover/mutation params
- ObjectiveDimensionMismatch error variant
- Add `Pruned` variant to `TrialState`
- Add `Error::TrialPruned` variant and standalone `TrialPruned` struct
with `From<TrialPruned> for Error` for ergonomic `?` usage
- Add `state` field to `CompletedTrial` (defaults to `Complete`)
- Add `Study::prune_trial()` and `Study::n_pruned_trials()`
- `optimize()` and `optimize_with_callback()` detect `TrialPruned`
errors via Any downcasting and record pruned trials instead of
failing them
- `best_trial()` / `best_value()` now filter to only `Complete` trials
- Re-export `TrialPruned` from crate root and prelude
Manuel Raimann