- Add blanket `impl Objective<V> for Fn(&mut Trial) -> Result<V, E>`
so closures work directly with `optimize`
- Rewrite optimize, optimize_async, optimize_parallel to accept
`impl Objective<V>` with before_trial/after_trial hooks
- Remove optimize_with, optimize_with_async, optimize_with_parallel
- Remove max_retries and retry logic from Objective trait
- Add explicit closure type annotations for HRTB inference
- Convert FnMut test closures to Fn via RefCell/Cell
- Sampler, pruner, storage, parameter, and multi_objective types are no
longer re-exported at the crate root; access via module paths instead
(e.g. optimizer::sampler::TpeSampler, optimizer::parameter::FloatParam)
- Prelude continues to re-export everything for convenience
- Add module-level pub use re-exports in sampler/mod.rs and parameter.rs
- Update derive macro to reference optimizer::parameter::Categorical
- Rename sampler::differential_evolution to sampler::de
- Fix all downstream imports in tests, benches, and doctests
- Fix all rustdoc intra-doc links to use explicit module paths
Extract shared evolutionary algorithm infrastructure (genetic operators,
candidate management, Das-Dennis reference points) from NSGA-II into a
new genetic.rs module, then build two new multi-objective samplers on top:
- NSGA-III: reference-point-based niching for well-distributed fronts
on 3+ objective problems (Das-Dennis structured points, normalization,
perpendicular distance association, niching selection)
- MOEA/D: decomposition-based optimization with three scalarization
methods (Tchebycheff, WeightedSum, PBI), weight-vector neighborhoods,
and neighborhood-based mating selection
Both implement MultiObjectiveSampler with builder pattern, seeded RNG,
and SBX crossover / polynomial mutation via the shared genetic module.
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
Manuel Raimann