`pareto_front` re-scanned every candidate from scratch. Track a
`dominated` bitset instead: whenever `i`'s scan finds `i` dominates `j`,
mark `j` so the outer loop skips `j` outright when it reaches it. The
inner check now reads both directions of `pareto_compare` — the
objective scan already computes both flags, so this is ~free.
Bit-identical, including under NaN-intransitive dominance: a mark is
only ever set from a direct pairwise `pareto_compare` result, never
inferred transitively. Also strict-or-neutral on work — the marks can
only ever let the outer loop *skip*, never add a scan.
Whole-program callgrind Ir for the compare_profile benchmark:
169,440,644,233 -> 165,311,562,939 (-2.44%); `pareto_front` self-Ir
44.1B -> 39.9B.
`pareto_front` was still the naive O(n²) formulation: a raw double loop
calling `pareto_compare` for every ordered pair, re-deriving feasibility
and the minimization-oriented objective values on every comparison.
Apply the same precompute pattern `non_dominated_sort` already uses:
hoist per-individual `feasible` / `violation` / `oriented` (a flat n*m
buffer) out of the loop, then run a branchless inlined dominance check
over the contiguous buffer. The kept set and its order are unchanged.
Whole-program callgrind Ir for the `compare_profile` benchmark:
221,836,742,708 -> 173,803,642,945 (-21.65%); `pareto_front` self-Ir
92.1B -> 44.1B.
Phase 1, tier 3 of the mutation-testing campaign — the shared Pareto /
metric / selection utilities used by every multi-objective algorithm.
A scoped cargo-mutants run found 75 survivors across these files; the
tests below target them.
- metrics/hypervolume.rs: dominates() boundary cases, non_dominated_
projection retained-set pins, hso_recursive 1-D/2-D base cases,
hypervolume_nd_from_evaluations empty/non-dominating skips.
- selection/tournament.rs: challenger_wins across the full feasibility
cross-product + equal-objective tie; better_by_objective and
better_by_feasibility branch pins; stochastic_ranking_select pf=0
feasibility ordering and count-wraps-modulo-population.
- pareto/crowding.rs: exact interior crowding distance on symmetric
and asymmetric fronts (pins the (next-prev)/span arithmetic).
- pareto/sort.rs: three-non-dominated-then-one-dominated and a strict
3-chain producing three singleton fronts.
- pareto/dominance.rs: trade-off → NonDominated, better-on-one-equal-
on-other → Dominates, identical → Equal.
- pareto/archive.rs: truncate boundary, trade-off kept alongside,
equal candidate rejected, smaller-violation infeasible eviction.
- pareto/front.rs: best_candidate keeps the first of tied minima.
- metrics/spacing.rs: exact spacing for a varying-NN-distance front.
src/core/problem.rs's lone survivor (decision_schema default body
'replace with vec![]') is an equivalent mutant — Vec::new() and vec![]
are identical — and is left in the residue.
Completes the rustdoc audit — every public item now has at least one
```rust example block in its docstring, exercised by
`cargo test --doc` (55 doctests, all passing).
- Operators: BitFlipMutation, SwapMutation, RealBounds,
GaussianMutation, BoundedGaussianMutation,
SimulatedBinaryCrossover, PolynomialMutation, LevyMutation,
ClampToBounds, ProjectToSimplex.
- Metrics: hypervolume_2d, hypervolume_nd, spacing.
- Pareto utilities: pareto_compare, pareto_front, best_candidate,
non_dominated_sort, crowding_distance, das_dennis,
ParetoArchive.
Each example is short (5-15 lines) and self-contained — copy-paste
into a fresh project and it runs.
`pareto_front` returns all candidates not dominated by any other in
input order (O(N²·M), acceptable for v1 per spec §9.3).
`best_candidate` is the single-objective "best" finder: returns None
unless there is exactly one objective; ignores infeasibles; returns None
if every candidate is infeasible (spec §9.4).
Both re-exported from the prelude.
swaits