The Deb fast non-dominated sort calls `pareto_compare` twice for
every (i, j) pair, and each `pareto_compare` call invokes
`ObjectiveSpace::as_minimization` twice — so for an N-point
population that's 4·N·(N-1) fresh `Vec<f64>` allocations per sort.
At N=100 with thousands of generations across the compare harness,
this dominated the per-generation cost of every Pareto-based MOEA.
Cache `as_minimization`/feasibility/violation once per individual
up front, then inline the dominance test against those cached
arrays. The output (per-pair dominance outcome and the per-i
`dominates` lists) is bit-identical to `pareto_compare`.
gungraun (instructions):
- non_dominated_sort_2d n=50: 852 317 → 198 574 (-77 %, 4.3×)
- non_dominated_sort_2d n=200: 13 513 271 → 2 601 813 (-81 %, 5.2×)
Wall-clock (compare harness, 10-seed mean):
- NSGA-II / ZDT1: 268 → 65 ms (4.1×)
- NSGA-II / ZDT3: 267 → 65 ms (4.1×)
- NSGA-II / DTLZ2: 344 → 106 ms (3.2×)
- NSGA-II / Rastrigin: 260 → 71 ms (3.7×)
- NSGA-III / DTLZ2: 318 → 122 ms (2.6×)
- NSGA-III / DTLZ1: 303 → 122 ms (2.5×)
- SMS-EMOA / DTLZ2: 1413 → 1369 ms (small additional win on top of HV)
- AGE-MOEA / DTLZ1: 430 → 229 ms (1.9×, on top of the AGE-MOEA caching)
- HypE / DTLZ2: 80 → 44 ms (1.8×)
Deb's fast non-dominated sort: returns Vec<Vec<usize>> of front indices
into the input population, with fronts[0] being the non-dominated set.
O(N²·M) is acceptable for v1 (spec §9.5).
Tests cover: small known population produces expected fronts; equal
candidates land on the same front; an empty population yields no
fronts.
swaits