docs(0.9): release notes, cookbook recipe, README polish
Companion to the feat(explorer) commit. Bumps the version and brings every cross-referencing doc up to v0.9 currency. - Cargo.toml: version 0.8.0 -> 0.9.0. - CHANGELOG: 0.9.0 entry covering the explorer export, the Problem-side metadata additions, the AlgorithmInfo trait, the pick_a_car example, and the new cookbook recipe. - README: closing paragraph of the PickACar example points users at the explorer with a one-call snippet (`ExplorerExport::from_result(...).with_algorithm_info(...) .to_file(...)?`). Version snippets bumped 0.8 -> 0.9. - New cookbook recipe at docs/book/src/cookbook/explorer.md covering: enabling the serde feature, enriching Problem with labels/units/decision-schema, the export call, the JSON schema, and custom decision-type handling. - SUMMARY.md and cookbook.md link the new recipe. - migration.md: new "To 0.9" section documenting the additive changes (purely backwards-compatible upgrade from 0.8.x). - introduction.md, comparison.md, choosing-an-algorithm.md, stability.md: version refs bumped 0.8 -> 0.9. - cookbook/parallel.md, cookbook/async.md: version refs bumped 0.8 -> 0.9. - getting-started.md: version refs bumped, serde feature description expanded to mention the explorer module. - SECURITY.md: supported-versions table moves to 0.9.x.
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@@ -14,17 +14,21 @@ project.
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optimizer await many evaluations concurrently. The differentiating
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feature vs other optimization libraries.
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- [Tune a model with expensive evaluations](./cookbook/expensive-evaluations.md)
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— `BayesianOpt`, `Tpe`, and `Hyperband` for the 50–500-eval
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— Bayesian Optimization, TPE, and Hyperband for the 50–500-eval
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regime.
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- [Compare two algorithms on your problem](./cookbook/compare.md) —
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multi-seed harness pattern straight from `examples/compare.rs`.
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- [Optimize a permutation (TSP-style)](./cookbook/permutation.md) —
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`AntColonyTsp` with a distance matrix.
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Ant Colony with a distance matrix.
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- [Constrain your search with `Repair`](./cookbook/constraints.md) —
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bounds, simplex projection, custom repair.
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- [Pick one answer off a Pareto front](./cookbook/pick-one.md) — the
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a-posteriori weighted-decision pattern from the `jiggly_tuning`
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example.
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- [Explore your results in a webapp](./cookbook/explorer.md) — export
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an `OptimizationResult` to JSON and browse it interactively at
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[heuropt-explorer](https://swaits.github.io/heuropt-explorer/) —
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parallel coordinates, scatter, range filters, weighted ranking.
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- [Write your own algorithm](./cookbook/custom-optimizer.md) —
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implement `Optimizer<P>` from scratch, à la the
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`examples/custom_optimizer.rs` walkthrough.
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