Adds heuropt-plot, a tiny SVG-only plotter that takes heuropt
results and emits scatter plots (pareto_front_svg) and line plots
(convergence_svg). No heavy 'plotters' or 'tiny-skia' dep — hand-
rolled SVG so the crate adds <100 KB to a build.
Workspace setup: root Cargo.toml gains [workspace] with members =
['.', 'heuropt-plot']. heuropt-plot has its own version (0.1.0) and
publishes independently against heuropt 0.8+.
Adds examples/visualize.rs that wires it up: NSGA-II on Schaffer
N.1, plain run() (no observer plumbing), final-front SVG written to
disk.
Adds the headline async/await capability for IO-bound evaluations
(HTTP services, RPC clients, spawned subprocesses) — the
differentiator vs pymoo / hyperopt / MOEA Framework.
No public-API breaks for synchronous users. The new surface is
gated behind a new `async` feature flag.
- core::async_problem::AsyncProblem trait (async fn evaluate_async).
- algorithms::parallel_eval_async::evaluate_batch_async helper using
futures::stream::FuturesOrdered with concurrency-bounded chunks;
preserves input order so seeded determinism holds when evaluations
are themselves deterministic.
- run_async on RandomSearch and DifferentialEvolution.
- examples/async_eval.rs: simulated 20 ms remote service. concurrency=1
→ 4.2 s, concurrency=4 → 2.1 s (2× speedup).
Bumps Cargo.toml to 0.8.0; CHANGELOG entry covers the above plus a
note that 0.6.0/0.7.0 on crates.io are yanked experimentals and 0.8
picks up cleanly from 0.5.
Theme: documentation and project polish. No public-API changes; this
is the v0.5 release that elevates heuropt's docs/onboarding/governance
to bar-setting status.
Adds:
- mdbook user guide at docs/book/ with intro, getting-started,
defining-problems, choosing-an-algorithm, cookbook (7 recipes),
comparison vs other libraries, stability/SemVer, migration guides.
Deploys to https://swaits.github.io/heuropt/ via .github/workflows/
docs.yml.
- Runnable rustdoc examples on every algorithm (35 of them), all
exercised by cargo test --doc.
- Three real-world examples: portfolio.rs (multi-obj with budget
constraint), hyperparam_tuning.rs (BO + TPE), scheduling.rs
(permutation via SA + SwapMutation against Smith's-rule oracle).
- Governance: CONTRIBUTING.md, SECURITY.md, CODE_OF_CONDUCT.md
(adopting builderscode.org's Builder's Code of Conduct), GitHub
issue templates, PR template.
Polishes:
- README hero with badges + user-guide link.
- lib.rs crate-level docs.
- CHANGELOG entry for 0.5.0.
Bumps Cargo.toml to 0.5.0.
CHANGELOG entry consolidates the unreleased work since v0.3.0:
testing-infrastructure expansion (proptest suites, cargo-fuzz
harness, stability tests, gungraun benches, CI), two real bug
fixes the testing surfaced (NaN-cycle non_dominated_sort, simplex
projection magnitude precision), the README decision-tree update
against the v0.3.0 comparison data, and the v0.4.0 perf pass
(cumulative compare harness 18.6 s → 5.7 s, 3.27×).
`examples/compare-results.md` refreshed with the post-perf-pass
ms numbers; quality metrics are bit-identical to the v0.3.0
snapshot (the perf pass was strictly CPU time, never algorithmic).
Cuts ~150 ms (-2.5 %) off the compare harness via better cross-crate
inlining of small Pareto/HV helpers. Costs ~20 s extra on a from-
scratch `cargo build --release`, but is essentially free on
incremental rebuilds.
Only applies when this crate is the workspace root (i.e. when
developing heuropt or running its own examples). Downstream users
who consume heuropt as a dependency see whatever profile their own
Cargo.toml configures.
Adds proptest as a dev-dependency and a `tests/properties.rs`
integration suite that probes invariants on randomly generated
inputs:
Pareto invariants:
- `pareto_compare` is anti-symmetric: A→B is opposite of B→A for
Dominates / DominatedBy
- `pareto_compare` is reflexive on equal candidates (returns Equal)
- `pareto_front` output is internally non-dominated
- `non_dominated_sort` puts every member into exactly one front
- `crowding_distance` returns Vec same length as front; boundary
points are infinity for fronts of size ≥ 2 in any axis-sortable
configuration
Operator invariants:
- `SimulatedBinaryCrossover` returns 2 children of the right length,
all in bounds
- `PolynomialMutation` returns 1 child of the right length, in bounds
- `BoundedGaussianMutation` returns 1 child in bounds
- `ClampToBounds` repair always lands in bounds
- `ProjectToSimplex` repair always sums to total and is non-negative
Algorithm invariants:
- For any seed, `Optimizer::run` is deterministic across two calls
- Final population has the documented size for population-based
algorithms
These are the invariants the existing 226 fixed-input unit tests
collectively check; proptest gives us coverage on inputs they don't
cover individually.
Wire `gungraun` 0.18 as a dev-dependency and a `benches/` directory
with instruction-count benchmarks for the algorithmic hot paths.
Why gungraun and not criterion: heuropt's hot paths are deterministic
numerical loops where wall-clock noise dominates real differences.
gungraun runs each benchmark under valgrind/callgrind once and reports
exact instruction counts — stable across machines and CI runners,
detects sub-microsecond regressions cleanly.
Benchmarks added:
- pareto::non_dominated_sort (the inner loop of every Pareto MOEA)
- pareto::crowding_distance (NSGA-II survival selection)
- metrics::hypervolume_nd (HSO recursion, used by SMS-EMOA)
- internal::cholesky (BO's per-step posterior factorization)
- algorithms::nsga2 single generation (end-to-end smoke check)
- algorithms::cma_es single generation (eigendecomposition cost)
Tracked size only — these aren't part of the regular CI matrix because
they need valgrind installed. Run with `cargo bench` locally.
Wired via the standard `[[bench]]` Cargo entries with `harness = false`
so gungraun's main_macro does the dispatch.
CHANGELOG entry for the v0.3.0 cohort, version bump in Cargo.toml and
README. Theme: filling heuropt's expensive-evaluation and constraint-
handling gaps.
Algorithms (9 new): OnePlusOneEs, NelderMead, IpopCmaEs, BayesianOpt,
SeparableNes, Tpe, Hyperband.
Operators (1 new): LevyMutation. Repair operators (1 trait + 2 impls):
Repair<D> with ClampToBounds and ProjectToSimplex.
Selection helpers (1 new): stochastic_ranking_select.
Internal helpers: Cholesky factorization (used by BO).
API additions:
- CmaEsConfig.initial_mean: Option<Vec<f64>> (None preserves existing
midpoint-of-bounds behavior; used by IpopCmaEs to inject restart
diversity).
- New PartialProblem trait — multi-fidelity contract used by
Hyperband.
No breaking changes to v0.2.0 public API.
Adds a `parallel` Cargo feature that pulls in rayon and parallelizes
the only step that's actually expensive in practice — calls to
`Problem::evaluate` — across the population. RNG-driven steps (parent
and donor selection, variation, replacement decisions) stay serial, so
seeded runs remain deterministic regardless of feature state, and the
default and `--features parallel` builds produce bit-identical
results.
Wiring:
- New `algorithms::parallel_eval::evaluate_batch` helper with two
cfg-gated implementations (rayon's `into_par_iter` when the feature
is on, plain `into_iter` otherwise). Both preserve input order, so
pareto_front and crowding-distance decisions remain reproducible.
- `RandomSearch`, `Nsga2`, and `DifferentialEvolution` now route
population/offspring evaluation through the helper. NSGA-II's main
loop is restructured into a serial selection-and-variation phase
followed by a parallel-friendly batch evaluation phase.
- DE's per-target loop is restructured into three phases (serial trial
construction → batch evaluation → serial replacement). Side effect
of the restructuring: DE is now the canonical synchronous DE/rand/1/bin
rather than the asynchronous variant where target `i+1` sees `i`'s
in-flight update. Synchronous is the textbook formulation, so this
is a small correctness improvement on top of the parallelism enable.
- PAES stays serial — its main loop has a sequential dependency on the
current candidate and would gain nothing from rayon.
Cost: algorithm impls now require `P: Sync` and `P::Decision: Send`
unconditionally so a single impl serves both feature modes. This is a
small bound tightening that any plain-data Problem already satisfies; in
return the public `Problem` trait itself stays unchanged and the
default build picks up no new dependencies.
Verified:
- `cargo test` and `cargo test --features parallel` both pass; the
Nsga2 `deterministic_with_same_seed` test confirms reproducibility.
- `cargo run --release --example benchmarks` and the same with
`--features parallel` produce bit-identical ZDT1 / Rastrigin
results.
- License the crate as MIT only.
- Fill in package description and `readme` field.
- Add rand 0.9 and rand_distr 0.5 (the `StdRng` and Normal sampler the
spec mandates as the single Rng type).
- Add optional serde 1 gated behind a `serde` feature flag for later
derives on core data types.
Initial state from `cargo new --lib` plus the technical design spec at
docs/heuropt_tech_design_spec.md, which is the source of truth for the
crate's public API and v1 acceptance criteria.
swaits