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chore(release): prepare v0.1.0 — Cargo metadata, CHANGELOG, README polish

- Cargo.toml: add `repository`, `homepage`, `documentation`,
  `keywords`, `categories`, `authors`, and `rust-version = "1.85"`
  (the version that stabilized edition 2024).
- CHANGELOG.md: new file in Keep-a-Changelog format with the full
  v0.1.0 inventory (core, traits, pareto utilities, operators,
  algorithms, metrics, examples, and the `serde`/`parallel` features).
- README.md: add crates.io / docs.rs / license badges and a Changelog
  link.

Pre-release verification (all clean):
- cargo build (default + --features parallel)
- cargo test (default, parallel, serde, --all-features) — 111 lib +
  3 doc tests pass under each.
- cargo clippy --all-targets --all-features -- -D warnings
- cargo doc --no-deps
- cargo package --no-verify → 57 files, 261 KB

2026-05-04 20:38:46 -06:00

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Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

Unreleased

0.1.0 — 2026-05-04

Initial release.

Core types and traits

Direction, Objective, ObjectiveSpace (with as_minimization direction conversion).
Evaluation with feasibility (constraint_violation <= 0.0).
Candidate<D>, Population<D>, OptimizationResult<D>.
type Rng = rand::rngs::StdRng and rng_from_seed so no public trait is generic over the RNG.
Problem, Optimizer<P>, Initializer<D>, Variation<D>.

Pareto utilities

pareto_compare, pareto_front, best_candidate, non_dominated_sort (Deb fast non-dominated sort), crowding_distance, ParetoArchive<D>, das_dennis (structured reference points for NSGA-III and MOEA/D).

Operators

Real: RealBounds, GaussianMutation, BoundedGaussianMutation, SimulatedBinaryCrossover (SBX), PolynomialMutation.
Binary: BitFlipMutation.
Permutation: SwapMutation.
CompositeVariation pipeline (typically crossover → mutation).

Selection helpers

select_random, tournament_select_single_objective.

Reference algorithms

RandomSearch — sample-evaluate-keep baseline.
Paes — small (1+1) Pareto Archived Evolution Strategy.
Nsga2 — canonical Pareto-based EA with crowding distance.
Nsga3 — many-objective NSGA-III with reference-point niching.
Spea2 — Strength Pareto Evolutionary Algorithm 2.
Moead — decomposition-based MOEA/D with the Tchebycheff scalar.
DifferentialEvolution — single-objective DE/rand/1/bin.

Metrics

spacing (Schott), hypervolume_2d (exact 2-D dominated hypervolume).

Examples

random_search, toy_nsga2, custom_optimizer — minimum-viable walkthroughs.
benchmarks — ZDT1 and Rastrigin reference runs.
compare — multi-seed comparison harness running every applicable algorithm on ZDT1 (2-obj), DTLZ2 (3-obj), and Rastrigin (single-obj), reporting hypervolume, spacing, mean L2, front size, and wall time.
jiggly_tuning — 4-objective NSGA-III tuning of the jiggly USB-mouse-jiggler firmware with an a-posteriori weighted-decision step that picks one recommendation off the Pareto front.

Optional features

serde — Serialize / Deserialize derives on the core data types.
parallel — rayon-backed parallel population evaluation in RandomSearch, Nsga2, and DifferentialEvolution. Seeded runs stay bit-identical to serial mode.

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