Commit c40e943
Batch-add 13 Backlog Models + 26 Backlog Rules (#1067)
* Add /auto-pipeline orchestrator + strengthen rule-issue quality gates
- New skill .claude/skills/auto-pipeline: orchestrator that drives one
Backlog issue from quality gate to Final review via fresh-context
subagents (check-issue, fix-issue, run-pipeline, review-pipeline).
Substantive issue-body problems are routed to codex xhigh; fundamental
flaws with no public reference park the issue on OnHold.
- check-issue: add Rule Check 5 (Completeness, fail label "Incomplete").
Mandatory literature research + codebase corner-case enumeration +
hand-tracing on >= 2 non-canonical instances for every [Rule] issue.
- review-structural: add Step 4b (Round-trip Execution, mandatory for
Rule reviews). Reviewer must run cargo test by name, paste the
"test result: ok" line, and confirm the test exercises the four
phases of a real round-trip.
- review-quality: promote "closed-loop without round-trip verification"
from a Minor flag to Critical, with explicit red flags
(is_some-only, target-side-only asserts, unique-optimum instances).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* Add MinimumDiscretePlanarInverseKinematics model (#994)
Robotics inverse-kinematics problem: given link lengths l_j, target
g in R^2, per-link sampled orientations Phi_j, and consecutive-pair
admissibility sets A_j, pick indices a_j in {0..m_j-1} with
(a_{j-1}, a_j) in A_j minimizing the squared end-effector distance
||sum_j l_j (cos phi_{j,a_j}, sin phi_{j,a_j}) - g||^2.
- src/models/misc/minimum_discrete_planar_inverse_kinematics.rs:
per-link dims (non-binary), Min<f64> objective, A_j feasibility
returns Min(None), declare_variants! default entry, ProblemSchemaEntry
+ ProblemSizeFieldEntry, canonical example_db spec via inventory.
- src/unit_tests/models/misc/...: creation, evaluate (feasible/
infeasible), brute-force solver, serialization roundtrip.
- problemreductions-cli/: new (f64,f64) and Vec<Vec<(usize,usize)>>
schema parsers; --link-lengths/--target-point/--orientation-samples/
--allowed-pairs flags via the schema-driven create path.
- docs/paper: problem-def block + display-name + worked example;
references.bib entries for Salloum2025 and DaiIzattTedrake2019.
Reference: Salloum et al., "Quantum annealing for inverse kinematics
in robotics", Scientific Reports 2025, doi:10.1038/s41598-025-34346-z.
Closes #994
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* Fix #994 model: complexity reflects total config product, not 2^n
The brute-force search space is prod_{j=1}^n m_j, not 2^n — per-link
sample counts m_j are arbitrary. Add a `total_configurations()` getter
that returns the product, and rewrite the declare_variants! complexity
as `num_links * total_configurations` (n vertices in evaluate cost
times the iteration space).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* Reformat total_configurations getter (cargo fmt)
Trivial single-line rewrite to match rustfmt.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* Add MaximumCoKPlex model (#1015)
Co-k-plex problem: given graph G=(V,E), vertex weights w, and integer
k>=1, find max-weight subset S subseteq V such that the induced
subgraph G[S] has maximum degree at most k-1 (i.e. every selected
vertex has at most k-1 selected neighbours). Generalizes
MaximumIndependentSet (the k=1 case) and is the complement-graph view
of maximum k-plex from the clique-relaxation literature.
- src/models/graph/maximum_co_k_plex.rs: MaximumCoKPlex<G,W,K>
parameterized by graph type, weight type, and K-multiplier. Only the
KN (runtime-k) variant registered initially per the issue's
"initially KN, K1/K2/... later" plan. Max<W::Sum> objective,
induced-degree feasibility, declare_variants! default + i32 variant,
canonical example via inventory (5-cycle weights (5,1,4,1,3) k=2,
optimum {0,2,4} value 12).
- src/unit_tests/models/graph/maximum_co_k_plex.rs: creation,
evaluate-feasible (issue optimum + smaller feasible), evaluate-
infeasible (degree-2 violation), brute-force solver, serialization.
- problemreductions-cli/src/commands/create/: schema-driven CLI maps
schema field bound_k to existing --k flag with semantic validation.
- docs/paper: problem-def block with C_5 worked example and k=1 ->
MaximumIndependentSet equivalence note; references.bib gains
Hernandez2016MolecularSimilarity and HosseinianButenko2022KDependent.
References: arXiv:1601.06693 (Hernandez et al., 2016) for the
molecular-similarity framing; doi:10.1016/j.dam.2021.10.015
(Hosseinian & Butenko, 2022) for the maximum k-dependent set view.
Closes #1015
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* Add MaximumCommonEdgeSubgraph model (#1018)
MCES: given two directed edge-labelled graphs G1, G2, find a partial
injective map f: U1 ⊆ V1 → V2 maximizing the number of preserved
labelled arcs (u, λ, v) ∈ E1 with f(u), f(v) defined and
(f(u), λ, f(v)) ∈ E2. Edge labels must match exactly; set semantics
(no multiplicities); disconnected common subgraphs allowed; no
secondary tie-break.
- src/models/graph/maximum_common_edge_subgraph.rs:
local LabelledArc + LabelledDigraph structs (does not extend the
existing Graph trait hierarchy in this PR). dims = vec![|V2|+1; |V1|]
with the +1 slot encoding ⊥. Max<i64> objective with injectivity
feasibility on the matched slots. ProblemSchemaEntry +
ProblemSizeFieldEntry for num_vertices_1/_2 and num_arcs_1/_2,
declare_variants! default with complexity (num_vertices_2+1)^num_vertices_1.
Canonical example via inventory from the issue's 5-vs-4-vertex
instance with optimum value 5.
- src/unit_tests/models/graph/maximum_common_edge_subgraph.rs:
12 tests covering creation, evaluate-feasible (optimum 5),
evaluate-injectivity-violated, evaluate-fewer-preserved, brute-force
solver, serialization.
- problemreductions-cli/: new --graph-1 / --graph-2 flags with a
LabelledDigraph parser; alias MCES.
- docs/paper: problem-def block, display-name, MCES worked example.
- docs/paper/references.bib: corrected per Crossref against the
check-issue warning — Bahiense2012 first names (Laura/Gordana/Breno),
Soule2021 author list (Soule/Reinharz/Sarrazin-Gendron/Denise/
Waldispuhl) and venue, Bokhari1981 volume (C-30).
References: doi:10.1109/TC.1981.1675756 (Bokhari 1981),
doi:10.1016/j.dam.2012.01.026 (Bahiense et al. 2012, polyhedral
investigation), doi:10.1371/journal.pcbi.1008990 (Soule et al. 2021,
RNA networks application).
The direct `MaximumCommonEdgeSubgraph -> ILP` rule (#1019) is out of
scope for this PR and will follow separately.
Closes #1018
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* Add MaximumEdgeWeightedKClique model (#1020)
Exact-cardinality edge-weighted clique: given a simple undirected
graph G=(V,E), edge weights w: E→R, and an integer k with 0≤k≤|V|,
find a vertex subset S with |S|=k forming a clique that maximizes
the sum of weights of edges induced by S. Edge weights may be
negative; k=0 and k=1 are admitted with objective value 0.
Distinct from the existing MaximumClique (vertex-weighted, no
exact-k) and KClique (decision problem with threshold |S|>=k).
- src/models/graph/maximum_edge_weighted_k_clique.rs:
MaximumEdgeWeightedKClique<W: WeightElement> with SimpleGraph fixed;
edge_weights vector aligned to graph.edges() order, runtime k field.
dims = vec![2; |V|]. Max<W::Sum> objective; infeasible when |S|≠k
or S is not a clique. declare_variants! default (SimpleGraph,i32)
plus (SimpleGraph,f64). Canonical example via inventory from the
issue's 4-vertex instance with negative weight (clique {0,1,2}
value 8 beats {0,1,3} value 6).
- src/unit_tests/models/graph/maximum_edge_weighted_k_clique.rs:
12 tests covering creation, evaluate-feasible (both optima),
evaluate-infeasible-wrong-size, evaluate-infeasible-not-clique,
brute-force solver, edge cases k=0 and k=1 (value 0), f64 variant,
serialization roundtrip, panic guards.
- docs/paper: problem-def block with worked example highlighting that
the optimum includes a negative edge; display-name entry; cites
Gouveia & Martins 2015 and Hunting/Faigle/Kern 2001.
- docs/paper/references.bib: Crossref-verified Gouveia2015MEWC
(author corrected to Pedro Martins, not Paulo as the issue body
said) and HuntingFaigleKern2001EWC.
References: doi:10.1007/s13675-014-0028-1 (Gouveia & Martins 2015,
sparse-graph compact formulations); doi:10.1016/S0377-2217(99)00449-X
(Hunting, Faigle & Kern 2001, Lagrangian relaxation).
The direct `MaximumEdgeWeightedKClique -> ILP` rule (#1021) is out
of scope for this PR and will follow separately.
Closes #1020
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* Add HighlyConnectedDeletion model (#1022)
Given a simple undirected graph G=(V,E), find a minimum-cardinality
edge set F ⊆ E such that every connected component of G - F is either
an isolated vertex or a highly connected graph on ≥3 vertices
(edge connectivity λ(H) > |V(H)|/2, strict). Components of size 2
are explicitly invalid. Weaker than clique-deletion: every K_k for
k≥3 is highly connected, but not every highly connected graph is a
clique.
- src/models/graph/highly_connected_deletion.rs: variables are EDGES
(x_e=1 means delete edge e). Min<i64> objective counts deletions;
infeasibility on any non-singleton component that is not highly
connected (and any 2-vertex component). Private edge_connectivity
helper computes λ via repeated max-flow with unit edge capacities
(fine for small components in tests). ProblemSchemaEntry,
ProblemSizeFieldEntry (num_vertices/num_edges), declare_variants!
default with complexity 2^num_edges. Canonical example via
inventory: K3 with leaf vertex 3 attached to 2 (4 vertices,
4 edges) — optimum deletes only (2,3), value 1.
- src/unit_tests/models/graph/highly_connected_deletion.rs: 17 tests
covering creation, evaluate-optimum, evaluate-zero-deletions-
infeasible, evaluate-delete-all-feasible, evaluate-infeasible
2-vertex-component and infeasible path-component, wrong-length
config guard, brute-force on canonical + a "double triangle"
discriminator instance (two K3's joined at a bridge — optimum 1)
to address the check-issue warning about example discriminatory
power, serialization, variant, plus edge_connectivity helper
tests (single vertex=0, single edge=1, P3=1, K3=2, K4=3).
- docs/paper: problem-def block with the K3-with-leaf worked example,
display-name entry; Crossref-verified BibTeX entries for Hüffner
et al. 2014 (TCBB) and Hartuv & Shamir 2000 (IPL), with proper
umlaut encoding H{"u}ffner per repo convention.
References: doi:10.1109/TCBB.2013.177 (Hüffner et al. 2014, partitioning
biological networks); doi:10.1016/S0020-0190(00)00142-3 (Hartuv &
Shamir 2000, HCS clustering algorithm).
The direct `HighlyConnectedDeletion -> ILP` rule (#1023) is out of
scope for this PR and will follow separately.
Closes #1022
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* Add EulerianPath model (#1024)
Classical directed-multigraph satisfaction problem: given D=(V,A) with
parallel arcs and loops allowed, decide whether a directed trail
exists that uses every arc exactly once. No start or end vertex is
fixed by the input. Empty-arc instance is accepted with the empty
trail; isolated vertices are ignored.
Polynomial-time solvable (O(num_vertices + num_arcs)) by the standard
Eulerian criterion plus Hierholzer construction, so this widens the
catalog beyond NP-hard problems.
- src/models/graph/eulerian_path.rs: EulerianPath { graph:
DirectedGraph }. dims = vec![m; m] where m = num_arcs (variable t
picks which arc occurrence is the t-th trail step); the brute-force
search space is m^m but the registry complexity reflects the
linear-time best-known algorithm. Or-typed feasibility: configuration
must be a permutation of {0..m-1} and consecutive arcs must chain
(end of arc t equals start of arc t+1). declare_variants! default
+ ProblemSchemaEntry + ProblemSizeFieldEntry. Canonical example via
inventory from the issue's 3-vertex 4-arc instance with parallel
arcs (yes-instance, witness config [0,2,3,1]).
- src/unit_tests/models/graph/eulerian_path.rs: 11 tests covering
creation, evaluate-valid-witness, evaluate-not-permutation,
evaluate-bad-trail, evaluate-out-of-range, evaluate-wrong-length,
brute-force yes (canonical) + brute-force no (the issue's 2-vertex
4-arc imbalanced counterexample), empty-arcs edge case (Or(true)
with the empty witness), serialization roundtrip, variant + name.
- problemreductions-cli/src/commands/create/schema_support.rs: wire
--graph (DirectedGraph) for EulerianPath via the existing parser.
- docs/paper: problem-def block with both the yes-instance and the
no-instance from the issue; display-name entry; references.bib gains
Crossref-verified BangJensenGutin2009Digraphs (J{\o}rgen Bang-Jensen,
o-slash) and Ebert1988ComputingEulerianTrails (J{"u}rgen Ebert,
u-umlaut) — corrected from the issue body's mojibake.
References: doi:10.1007/978-1-84800-998-1 (Bang-Jensen & Gutin 2009,
digraphs); doi:10.1016/0020-0190(88)90170-6 (Ebert 1988, computing
Eulerian trails).
The direct `EulerianPath -> ILP` rule (#1025) is out of scope for
this PR and will follow separately.
Closes #1024
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* Add PrizeCollectingSteinerForest model (#1026)
Biology-paper prize-collecting Steiner forest: given a network G with
nonnegative vertex prizes p(v), nonnegative edge costs c(e), and
tradeoff coefficients beta, omega, find a forest subgraph
F = (V_F, E_F) minimizing
beta * sum_{v notin V_F} p(v) + sum_{e in E_F} c(e) + omega * kappa(F)
where kappa(F) is the number of tree components (singleton selected
vertices count). Generalizes prize-collecting Steiner tree from one
connected tree to a forest; the artificial-root trick is deliberately
kept out of the base model and will live in the companion reduction
rule.
- src/models/graph/prize_collecting_steiner_forest.rs:
PrizeCollectingSteinerForest<G, W> with dims = vec![2; n+m] (vertex
bits then edge bits), Min<W::Sum> objective. Feasibility checks
edges-incident-to-selected-vertices and forest acyclicity; infeasible
→ Min(None). Canonical example via inventory from the issue's
3-vertex path with optimum [1,1,1, 1,0] value 5 (cost 1 + omega*2
components). declare_variants! default (SimpleGraph,i32) plus
(SimpleGraph,f64). Complexity 2^(num_vertices+num_edges).
- src/unit_tests/models/graph/prize_collecting_steiner_forest.rs:
13 tests — creation, evaluate-optimum, evaluate-full-path (value 9),
evaluate-three-singletons (value 6), evaluate-empty-forest
(value 12), evaluate-edge-without-endpoint-infeasible,
evaluate-cycle-infeasible (triangle selected entirely),
brute-force solver, serialization, f64 variant, panic guards.
- problemreductions-cli/: new --vertex-prizes / --edge-costs / --beta /
--omega flags via schema-driven create; mapping and fixture updates.
- docs/paper: problem-def block with worked example breakdown
(omitted-prize / edge-cost / component terms summing to 5);
display-name; Crossref-verified BibTeX for both Tuncbag et al.
papers (JCB 2013 and RECOMB 2012).
References: doi:10.1089/cmb.2012.0092 (Tuncbag et al. 2013, JCB);
doi:10.1007/978-3-642-29627-7_31 (Tuncbag et al. 2012, RECOMB).
The direct `PrizeCollectingSteinerForest -> SteinerTree` rule (#1027)
is out of scope for this PR and will follow separately.
Closes #1026
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* Add MinimumCostMaximumFlow model (#1029)
Lexicographic objective on a directed multigraph with source s, sink t,
arc capacities u_e, and arc costs c_e: first maximize the s-t flow
value |f|, then among maximum-value flows minimize total arc cost
sum_e c_e f_e. Captures the CellRouter (Lummertz da Rocha et al. 2018)
model directly.
Architectural carve-out: the repo's Problem trait is discrete, so the
implementation restricts to INTEGRAL flows with dims=[c_e+1; m]. This
mirrors the existing MinimumEdgeCostFlow precedent and stays sound
for any rational instance by scaling. Documented in the module doc.
Lex encoding: Min<i64> with combined scalar
score = M * (max_possible_flow - flow_value) + cost
where M = sum_e c_e * u_e + 1 dominates any feasible cost — so lower
scores always prefer higher flow value first, breaking ties by lower
cost. Infeasible (capacity / conservation violations) → Min(None).
- src/models/graph/minimum_cost_maximum_flow.rs:
MinimumCostMaximumFlow { graph: DirectedGraph, source, sink,
capacities: Vec<i64>, costs: Vec<i64> }. Inherent helpers
flow_value(config) and total_cost(config) for tests. Canonical
example via inventory: V={0,1,2,3}, arcs [(0,1),(0,2),(1,2),
(1,3),(2,3)], capacities [2,1,1,1,2], costs [1,0,0,1,2] — optimum
config [2,1,1,1,2] with value 3 and cost 7. ProblemSchemaEntry +
ProblemSizeFieldEntry (num_vertices, num_arcs). declare_variants!
default with complexity (num_vertices+num_arcs)^6 (a conservative
polynomial placeholder justified by the LP formulation).
- src/unit_tests/models/graph/minimum_cost_maximum_flow.rs: 9 tests
covering creation, evaluate-optimum, evaluate-suboptimal-feasible,
evaluate-capacity-exceeded (infeasible), evaluate-conservation-
violated (infeasible), brute-force solver returning value 3 cost 7,
serialization, and the lex-tiebreaker test on a 4-vertex bottleneck
instance where two distinct max-value flows (value 1) exist with
costs 1 and 5 — brute-force must pick the cheaper one. The
tiebreaker test directly addresses the check-issue warning that
the original example admits a unique max-flow.
- problemreductions-cli/: new --source / --sink (usize) flags wired
via schema-driven create; --graph (DirectedGraph), --capacities,
--costs reused from the MECF wiring.
- docs/paper: problem-def block explaining the lex objective and the
integral-flow restriction, worked example with value/cost
breakdown; display-name; Crossref-verified BibTeX for
Lummertz da Rocha et al. 2018 (doi:10.1038/s41467-018-03214-y);
MIT 6.854 min-cost-flow notes as a @misc entry with URL.
References: doi:10.1038/s41467-018-03214-y (CellRouter, Nature Comms
2018); MIT 6.854 scribe notes for the standard min-cost-flow
equivalence.
The direct `MinimumCostMaximumFlow -> MinimumCostCirculation` rule
(#1031) is out of scope for this PR and will follow separately.
Closes #1029
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* Add MinimumCostCirculation model (#1030)
Classical minimum-cost circulation on a directed multigraph with
finite arc capacities u_e ≥ 0 and signed arc costs a_e ∈ R: find
g: E→R_{≥0} satisfying capacity bounds (0 ≤ g_e ≤ u_e) and flow
conservation at every vertex, minimizing sum_e a_e g_e.
This is the exact companion target for `MinimumCostMaximumFlow`
(reduction #1031) — the standard MCMF → MCCirc reduction uses a
sufficiently negative return arc from sink to source, which is why
signed costs must be supported in the base model.
Architectural carve-out (same as MinimumCostMaximumFlow #1029 and
MinimumEdgeCostFlow): the discrete Problem trait restricts to
INTEGRAL circulation with dims=[c_e+1; m]; sound for any rational
instance by scaling. Documented in the module doc.
- src/models/graph/minimum_cost_circulation.rs:
MinimumCostCirculation { graph: DirectedGraph, capacities: Vec<i64>,
costs: Vec<i64> } — no source/sink, conservation at every vertex.
Min<i64> objective; capacity-or-conservation violations → Min(None).
ProblemSchemaEntry + ProblemSizeFieldEntry (num_vertices, num_arcs).
declare_variants! default with conservative polynomial placeholder
(num_vertices+num_arcs)^6. Canonical example via inventory — a
3-vertex two-cycle instance discriminating between four feasible
alternatives (zero, cycle-A-only -2, cycle-B-only -3, both at
capacity -5) so round-trip tests have real discriminatory power,
addressing the check-issue warning about the issue's 2-vertex
example being too small.
- src/unit_tests/models/graph/minimum_cost_circulation.rs: 11 tests
covering creation, evaluate-optimum (config [2,2,1,1] → Min(-5)),
evaluate-zero, evaluate-cycle-A-only (-2), evaluate-cycle-B-only
(-3), evaluate-half-cycle-A (-4), evaluate-infeasible (capacity
exceeded, conservation violated), brute-force solver, serialization,
negative-cost-only-cycle smoke.
- problemreductions-cli/: --graph (DirectedGraph), --capacities,
--costs reused from MECF/MCMF wiring; new schema mapping for MCCirc.
- docs/paper: problem-def block with the two-cycle worked example
spelled out (per-unit costs, capacity bottlenecks), display-name
entry; reuses the existing mit6854MinCostFlow @misc bib entry
added with MCMF — no new references.bib changes.
References: MIT 6.854 (S2021) min-cost flow algorithms notes (shared
with #1029).
The direct `MinimumCostMaximumFlow -> MinimumCostCirculation` rule
(#1031) is out of scope for this PR and will follow separately.
Closes #1030
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* Add ClosestString model (#1032)
Consensus-string problem under Hamming distance: given an alphabet
Σ = {0,...,q-1} and n equal-length strings s_1,...,s_n ∈ Σ^m, find a
center string c ∈ Σ^m minimizing max_i d_H(c, s_i). NP-hard (Frances
& Litman 1997, Lanctot et al. 1999), with extensive FPT and PTAS
literature (Gramm & Niedermeier 2003, Ma & Sun 2009, Li/Ma/Wang 2002).
Distinct from ClosestSubstring — every input string has the same
length as the center, so there is no window-selection decision.
- src/models/misc/closest_string.rs: ClosestString { alphabet_size,
strings: Vec<Vec<usize>> }. Validating constructor panics on
length mismatch or out-of-alphabet symbol. dims = vec![q; m].
Min<i64> objective (always feasible — every config in the cube is
a syntactically valid center). Inherent getters alphabet_size,
num_strings, string_length, total_length. ProblemSchemaEntry +
ProblemSizeFieldEntry with all four size fields. declare_variants!
default with complexity alphabet_size^string_length. Canonical
example via inventory from the issue's 4-string binary length-3
instance (optimal center [0,0,0], radius 2).
- src/unit_tests/models/misc/closest_string.rs: 11 tests covering
creation, evaluate at three different centers (c=000 → 2, c=100
→ 3, c=111 → 3), brute-force solver returning radius 2 over 8
candidates, three panic guards (empty input, length mismatch,
out-of-alphabet symbol), a q=3 length-2 ternary smoke test
(radius 2 over 9 candidates), and serialization.
- problemreductions-cli/: schema-driven create wires --alphabet-size
(usize) and --strings (Vec<Vec<usize>>) — reuses the existing
Vec<Vec<usize>> parser added with #994.
- docs/paper: problem-def block with all four Hamming distances
spelled out for c=000; display-name entry; Crossref-verified
Li/Ma/Wang 2002 (JACM) bib entry.
Reference: doi:10.1145/506147.506150 (Li, Ma & Wang 2002, JACM).
The direct `ClosestString -> ILP` rule (#1034) is out of scope for
this PR and will follow separately.
Closes #1032
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* Add ClosestSubstring model (#1033)
Window-selection generalization of ClosestString (#1032): given an
alphabet Σ, n strings (NOT necessarily equal length), and a substring
length ℓ, find a center c ∈ Σ^ℓ and start positions p_i selecting
length-ℓ windows s_i[p_i .. p_i+ℓ) minimizing
max_i d_H(c, s_i[p_i .. p_i+ℓ)).
Motif-discovery model — NP-hard, no PTAS in general (Li, Ma & Wang
2002 JACM; Marx 2008).
ClosestString is the special case where every input string has
length exactly ℓ (single window per string).
- src/models/misc/closest_substring.rs: ClosestSubstring {
alphabet_size, strings: Vec<Vec<usize>>, substring_length }.
Validating constructor panics on empty input, substring_length >
min |s_i|, or out-of-alphabet symbol. dims concatenates ℓ center
slots (domain {0..q-1}) with n window-start slots (domain
{0..W_i-1} where W_i = |s_i| - ℓ + 1). Min<i64> objective, always
feasible since every config in the cube is syntactically valid.
Inherent getters alphabet_size, num_strings, substring_length,
total_length, total_num_windows, num_window_choice_product (with
saturating multiplication). ProblemSchemaEntry +
ProblemSizeFieldEntry. declare_variants! default with complexity
alphabet_size^substring_length * num_window_choice_product.
Canonical example via inventory from the issue's 3 binary strings
with ℓ=3 — optimum center [0,1,0] with window picks (0,1,0),
radius 1 over 216 candidate configs.
- src/unit_tests/models/misc/closest_substring.rs: 11 tests covering
creation, evaluate at optimum (radius 1), evaluate at center
[0,0,0] with all-zero windows (radius 2), evaluate at center
[1,1,1] (radius >=1), brute-force solver, ClosestString reduction
validation (substring_length = string_length → matches the #1032
canonical's radius 2), three panic guards (empty input, length
mismatch, out-of-alphabet symbol), and serialization roundtrip.
- problemreductions-cli/: schema-driven create wires
--alphabet-size + --strings (reused from #1032) plus the new
--substring-length (usize) flag.
- docs/paper: problem-def block with the worked example listing all
three window picks and per-window Hamming distances; display-name
entry. Reuses the existing Li/Ma/Wang 2002 JACM BibTeX entry
added with #1032 — no references.bib changes.
Reference: doi:10.1145/506147.506150 (Li, Ma & Wang 2002, JACM)
shared with #1032.
The direct `ClosestSubstring -> ILP` rule (#1035) is out of scope
for this PR and will follow separately.
Closes #1033
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* Add MaximumContactMapOverlap model (#1043)
Classical protein-structure contact-map alignment: given two ordered
contact graphs G_1=(V_1,E_1) and G_2=(V_2,E_2), find an order-preserving
partial injective map f: V_1 → V_2 ∪ {unmatched} maximizing the number
of contacts {i,k} ∈ E_1 such that both i, k are matched and
{f(i), f(k)} ∈ E_2. Aliases: CMO, MaxCMO.
NP-hard with substantial literature on exact algorithms and integer
programming (Andonov, Malod-Dognin & Yanev 2011; Xie & Sahinidis 2007).
- src/models/graph/maximum_contact_map_overlap.rs:
MaximumContactMapOverlap { num_vertices_1, contacts_1, num_vertices_2,
contacts_2 }. Validating constructor normalizes each pair to sorted
form (u<v), rejects self-loops, duplicates, and out-of-range
endpoints. dims = vec![num_vertices_2 + 1; num_vertices_1] (value 0
encodes unmatched; value j+1 maps to vertex j of G_2). Max<i64>
objective; non-injective or non-order-preserving matched values →
Max(None). ProblemSchemaEntry + ProblemSizeFieldEntry; inherent
getters num_vertices_1/_2 and num_contacts_1/_2. declare_variants!
default with complexity (num_vertices_2+1)^num_vertices_1.
Canonical example via inventory: G_1 with 4 vertices and contacts
{(0,2),(1,3)}, G_2 with 5 vertices and contacts {(0,2),(0,3),(1,4)}
— optimum [1,2,4,5] preserves both contacts → Max(Some(2)).
- src/unit_tests/models/graph/maximum_contact_map_overlap.rs: 17 tests
covering creation, evaluate at optimum, all-unmatched, single-match,
non-injective Max(None), non-order-preserving Max(None), suboptimal
feasible (config [1,2,3,4] preserves 1 of 2 contacts), brute-force
solver returning Max(2), wrong-length and out-of-range guards,
serialization, alias resolution for CMO/MaxCMO, and three panic
guards (self-loop, duplicate contact, endpoint out of range).
- problemreductions-cli/: schema-driven create wires --num-vertices-1
/ --num-vertices-2 / --contacts-1 / --contacts-2 (Vec<(usize,usize)>
parser) via the existing CreateArgs + flag_map + tests fixture.
- docs/paper: problem-def block with the alignment table and the two
preserved-contact bullets; display-name; Crossref-verified BibTeX
for both Andonov-Malod-Dognin-Yanev 2011 and Xie-Sahinidis 2007
JCB papers (with N{\"o}el encoded per repo umlaut convention).
References: doi:10.1089/cmb.2009.0196 (Andonov, Malod-Dognin & Yanev
2011, JCB); doi:10.1089/cmb.2007.R007 (Xie & Sahinidis 2007, JCB).
The direct `MaximumContactMapOverlap -> ILP` rule (#1044) is out of
scope for this PR and will follow separately.
Closes #1043
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* Trim skill redundancies surfaced by self-review of #1067
Net -83 lines across the four skill files touched by 694ef0c8.
auto-pipeline (-79):
- Collapse Step 0a + 0b into a single picker block; the only
difference was "filter by number" vs "sort and pick top" — now
branched by whether the ISSUE env var is set.
- Extract the boilerplate that was duplicated across all five
subagent prompts (output-only-JSON-block contract, universal don'ts,
malformed-JSON retry policy, severity vocabulary) into a single
"Subagent Contract" section near the top. Each prompt now states
only its scope and JSON shape. Drop the trailing "Reporting
Contract" section (merged into the new one).
- Trim the Board states table from 8 GraphQL IDs to the 3 columns
the orchestrator actually writes (ready, on-hold, plus the Backlog
it reads in Step 0). The IDs for In Progress / Review pool /
Under review / Final review live in run-pipeline / review-pipeline
where they are used.
- Drop three rows from Common Mistakes that just echoed the spec
(codex retry cap, increment SUBSTANTIVE_RETRIES, re-check after
auto-fix); keep only the non-obvious cross-cutting traps.
check-issue (-9 net):
- Rule Check 5a no longer re-lists the literature fallback chain;
one-line reference to Check 3c suffices.
- Rule Check 5c verdict table drops the (severity: ...) annotations
on Fail rows — severity classification is owned by auto-pipeline's
Subagent Contract, not by check-issue itself.
- Rule Check 5c drops the "cited reference does not contain the
reduction" row that explicitly admitted overlap with Check 3c;
add a one-line note that 3c handles that case.
review-structural (-19):
- Step 4b-4 (pred --via spot-check) was hedged out of its own
purpose with a "fall back to 4b-2" escape hatch. Rewrite as a
short focused step that uses pred --via when wired and is skipped
(with a note) otherwise — no padding.
review-quality (~2 net):
- Replace the 4-criterion expansion of the round-trip rule (which
was copy-pasted from review-structural Step 4b-3) with a single
pointer to that source-of-truth section. Per the existing
feedback_skill_no_duplication memory.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* Address final-review findings on #1067
- MinimumDiscretePlanarInverseKinematics: simplify complexity
string from "num_links * total_configurations" to
"total_configurations" so it matches issue #994's stated
O(prod_{j=1}^n m_j) baseline literally (the extra num_links
factor was per-config feasibility-check work, not configs).
- MinimumCostCirculation: add test_minimum_cost_circulation_issue_example_1030
that constructs issue #1030's verbatim 2-vertex example (arcs
0->1 cap=2 cost=3 and 1->0 cap=1 cost=-5, optimum -2). The
existing richer 3-vertex canonical instance is kept as the
primary discriminator.
* Add Partition -> IntegralFlowWithMultipliers reduction (#363)
Adds Sahni's multiplier-flow gadget: each Partition element becomes an item
vertex whose multiplier amplifies a binary source choice into either 0 or a_i
units entering a relay. A single bottleneck arc of capacity S/2 converts the
target's "net inflow at least R" condition into the exact equality needed by
Partition. Odd-S inputs reduce to a fixed infeasible 3-vertex instance.
- src/rules/partition_integralflowwithmultipliers.rs: reduction impl with
odd-S/even-S branches and witness extraction from source arcs
- src/unit_tests/rules/partition_integralflowwithmultipliers.rs: 5 tests
(closed-loop, structure on even-total YES, even-total NO exercises
bottleneck, odd-total fixed NO, witness extraction)
- src/rules/mod.rs: register module and example specs
- docs/paper/reductions.typ: full theorem with construction, correctness
proof, and worked example using the canonical fixture
Closes #363.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add MinimumVertexCover -> ComparativeContainment reduction (#385)
Plaisted (1976) reduction from Decision Minimum Vertex Cover to
Comparative Containment (Garey & Johnson SP10). Given a unit-weight VC
instance (G = (V, E), K), the universe X = V is encoded as:
- For each vertex v, a reward set R_v = V \\ {v} with weight 1, so the
total R-weight equals n - |Y|.
- For each edge e = {u, v}, a penalty set S_e = V \\ {u, v} with weight
n + 1 that dominates the maximum possible reward whenever the edge is
uncovered.
- One budget set S_0 = V with weight n - K, which encodes the bound
through the resulting inequality K - |Y| >= (n + 1) * (#uncovered).
Source assertions mirror decisionminimumvertexcover_hamiltoniancircuit.rs:
unit weights are required, a negative bound emits a fixed unsatisfiable
target, and K >= n is handled as a trivial-YES instance (empty universe,
no R/S sets). Adds a ProblemSizeFieldEntry for ComparativeContainment
since it had no declared size_fields, and a paper theorem entry. Eight
unit tests cover structure counts, closed-loop YES/NO, witness
extraction, both trivial-YES branches, the trivial-NO branch, and the
weight-assertion guard.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add MinimumDiscretePlanarInverseKinematics -> QUBO reduction (#995)
Implements Salloum et al. 2025 quantum-annealing IK encoding: one-hot
binary lifting of sampled orientations, quadratic position-error term,
one-hot exactly-one penalty, and pair-feasibility penalty for forbidden
adjacent (a,b) pairs. Penalty constants are chosen above the maximum
possible position-error savings, so every QUBO minimizer decodes to a
feasible source configuration.
Also adds num_orientation_samples() getter on the source model.
Closes #995.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add OptimalLinearArrangement -> SequencingToMinimizeWeightedCompletionTime reduction (#472)
Implements Lawler 1978 precedence-constrained 1||sum w_j C_j encoding:
each vertex becomes a unit-length task with weight 1, each edge becomes
a zero-length task with weight 1, and the precedence constraints
enforce the OLA ordering. The minimum weighted completion time recovers
the OLA objective plus an additive shift d_max*n*(n+1)/2.
Also relaxes the target model's validator to allow zero-length edge
jobs needed by Lawler's construction.
Closes #472.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add ThreeDimensionalMatching -> ThreeMatroidIntersection reduction (#857)
Direct partition-matroid embedding: a 3DM matching is precisely the
common independent set of three partition matroids, one over each
coordinate axis (X, Y, Z). The reduction copies the triple set, builds
the three partition matroids by grouping triples that share each
coordinate, and uses identity solution extraction.
Closes #857.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add MinimumCoveringByCliques -> MinimumIntersectionGraphBasis reduction (#848)
Identity instance mapping: a clique cover {C_1, ..., C_k} of G is a
valid intersection-graph basis with the same cardinality k, since each
vertex's labels are exactly the cliques it belongs to and each edge
is witnessed by a shared label. The witness extraction labels each
edge by a shared intersection slot.
Closes #848.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add Numerical3DimensionalMatching -> NumericalMatchingWithTargetSums reduction (#827)
Standard G&J transformation: a Numerical 3DM instance with triples
(X, Y, Z, bound) maps to an NMTS instance where the X and Y triples
form the pair sizes and each Z element becomes a target sum equal to
bound + z. The witness is recovered by multiset matching against the
source's third coordinate. Source u64 sizes are checked-cast to i64
with a documented overflow guard.
Closes #827.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add MaximumCoKPlex -> ILP reduction (#1016)
Direct boolean ILP encoding for the Co-k-Plex problem: each vertex gets
a binary variable, the objective maximizes the weighted sum, and a
per-vertex constraint bounds the induced degree by k - 1 using the
linear inequality sum_{u in N(v)} y_u <= (k - 1) + M * (1 - y_v).
Closes #1016.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add MaximumCommonEdgeSubgraph -> ILP reduction (#1019)
Boolean ILP encoding finds a one-to-one vertex correspondence between
G1 and G2 that maximizes the number of preserved edges. Variables x[i,k]
encode whether v_i in G1 maps to v_k in G2, with row/column sum-at-most-1
constraints enforcing a partial injection, and edge-preservation variables
y[(i,j),(k,l)] linearized via the standard product-with-binaries pattern.
Closes #1019.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add MaximumEdgeWeightedKClique -> ILP reduction (#1021)
Boolean ILP encoding with vertex selectors x_v, edge selectors y_uv via
McCormick linearization, an exact-cardinality constraint sum x_v = k,
and non-edge clique constraints x_u + x_v <= 1 for every non-edge.
The lower-bound McCormick inequality is essential because edge weights
may be negative.
Closes #1021.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add HighlyConnectedDeletion -> ILP reduction (#1023)
Set-partitioning ILP encoding: each candidate cluster is a feasible
highly-connected vertex subset (verified via edge-connectivity > n/2),
and a partition constraint forces each vertex to belong to exactly one
selected cluster. The objective minimizes the number of deleted edges
(those whose endpoints are in different clusters).
Also exposes pub(crate) helpers is_feasible_cluster and
induced_edge_count on the source model.
Closes #1023.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add EulerianPath -> ILP reduction (#1025)
MTZ-style ILP encoding for EulerianPath: integer variables y_{a,b}
encode compatible arc-pair successions, plus per-arc start/end/position
variables. Constraints enforce in-degree/out-degree balance for the
Eulerian trail, unique start/end arcs, and a position-strict ordering
that prevents subtours. The empty-arc source instance maps to the
empty ILP.
Closes #1025.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add MinimumCostMaximumFlow -> MinimumCostCirculation reduction (#1031)
Textbook reduction: keep all original arcs unchanged, append a return
arc (t, s) with capacity U = sum_{e in delta^+(s)} u_e and cost
-(1 + sum_e c_e). The deeply negative return-arc cost makes maximizing
flow on (t, s) the priority — i.e. the circulation must saturate
s -> t flow before optimizing residual cost. Solution extraction
discards the return arc.
Closes #1031.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Fix #995 example-db test compile error
Replace serde_json::json! comparisons with plain Vec<usize> values
to match the SolutionPair.source_config/target_config field types.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add ClosestString -> ILP reduction (#1034)
Position-character ILP encoding for ClosestString: binary variables
x_{j,a} encode the consensus string character at position j (with
one-hot assignment constraints), and a single integer radius variable
R is bounded by per-string Hamming-distance constraints. The objective
minimizes R.
Closes #1034.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add ClosestSubstring -> ILP reduction (#1035)
Position-character ILP encoding for ClosestSubstring: binary variables
x_{r,a} for the center substring's character at each position, window
choice indicators y_{i,p} (exactly one window per source string), and
an integer radius R bounded by per-window Hamming-distance constraints
plus a tight R <= ell upper-bound constraint critical for ILP solver
performance.
Closes #1035.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Fix clippy identity_op in closestsubstring_ilp test (#1035)
Replace `6 + 0` and `6 + 6 + 0` with `6` and `6 + 6`. Surfaced during
structural review of #363 commit (the lint blocks
`cargo clippy --all-targets -- -D warnings`).
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Fix incorrect expected value in zero-length-task test (#472 review)
The relaxed-validator test asserted Min(14) but the actual weighted
completion time for lengths [0,1,3], weights [3,5,1], schedule [0,1,2]
is 3*0 + 5*1 + 1*4 = 9. Surfaced during structural review of #472.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add canonical example for ThreeDimensionalMatching -> ThreeMatroidIntersection (#857 review)
Surfaced during structural review: rule was missing
canonical_rule_example_specs() and was not extended into the rule
example aggregator in mod.rs. Adds the q=3 5-triple feasible instance
from the closed-loop test as the canonical example.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Fix missing canonical examples + bib keys (#1021 review)
Surfaced during structural review of #1021:
- MaximumEdgeWeightedKClique has both i32 and f64 ReduceTo impls but
only an i32 canonical example was registered; the example-db
coverage test failed. Add an f64 spec mirroring the i32 instance.
- MaximumCoKPlex has both i32 and One ReduceTo impls but only an i32
canonical example existed (also flagged by the coverage test). Add
a One-weighted spec on the same C5 graph.
- Paper cited `@ParkLeePark1996EWClique` and `@GouveiaMartins2015EWClique`
but neither bib key existed. Add both entries to references.bib
while keeping the original `@GouveiaMartins2015MEWC` entry that the
problem-def section still cites.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Remove stale zero-length CLI tests after validator relaxation (#472)
PR #472 (commit f13bbb3d) relaxed
SequencingToMinimizeWeightedCompletionTime's validator to accept
zero-length tasks for the Lawler OLA reduction. Two CLI tests still
asserted the removed "task lengths must be positive" rejection, so CI
broke on the workspace test job. The new accept-zero-length semantics
are positively covered by unit tests in
src/unit_tests/models/misc/sequencing_to_minimize_weighted_completion_time.rs.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Fix paper compile errors: typst inter, missing/typo'd bib keys
Three mechanical paper-build fixes:
- Replace math-mode `intersect` with Typst's `inter` (set-intersection)
in the MinimumCoveringByCliques → MinimumIntersectionGraphBasis proof
(5 occurrences on lines 18087-18091).
- Drop orphan citation @deGastinesKnippel2024MCES from
MaximumCommonEdgeSubgraph → ILP (no matching bib entry; the rule still
cites the valid @Bahiense2012MCES McCormick formulation).
- Fix typo @lawler1978a → @lawler1978 on the OLA →
SequencingToMinimizeWeightedCompletionTime rule.
The first CI run was masked by the cli_tests failure (set -e); now that
tests pass, the paper compile step exposed these issues.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add auto-pipeline integration gate (Step 2.5)
PR #1067 hit two CI failures the per-item phases could not see:
- Two CLI integration tests asserted a model-validator behaviour that
the new OLA -> SequencingToMinimizeWeightedCompletionTime reduction
intentionally relaxed; closed-loop and unit tests for the new rule
all passed.
- `make paper` blew up on `intersect` (Typst expected `inter`), an
orphan bib key, and a typo'd key; no phase ran the Typst compile.
Adds an orchestrator-owned Step 2.5 that runs
`cargo test --workspace --features "ilp-highs example-db"` and
`make paper` on PR HEAD between Phase 2 (run-pipeline) and Phase 3
(review-pipeline). Any failure parks the card on OnHold for human
triage — codex rescue is not appropriate because the failing artefact
lives outside the issue's files.
In batch mode (multiple issues stacked on one branch with the PR
opened at the end), this gate is the only thing that catches
accumulated cross-item breakage before review.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Slim down auto-pipeline Step 2.5
CI-class failures (stale tests, typo'd bib keys, math-mode typos) are
small and mechanical; hand them straight to codex-rescue with a one-line
failure summary rather than walking the orchestrator through a long
JSON contract, PR-comment template, and explicit OnHold dance. Re-run
Step 2.5 once after codex; OnHold only if still failing.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Renumber auto-pipeline integration gate as Step 3 (not 2.5)
Bumps review-pipeline to Step 4. Diagram, intro paragraph, cross-step
references, and Common Mistakes table updated accordingly.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Revert review-structural Step 4b; let auto-pipeline Step 3 cover it
Step 4b mixed three different concerns into review-structural (a
read-only structural skill):
- 4b-2 ran `cargo test --exact <closed_loop>` for the new rule —
redundant with auto-pipeline Step 3's workspace-wide `make check`.
- 4b-3 read the test source to score it against four criteria — that's
a test-quality judgment, not a structural check; review-quality is
the right home for that and it already covers test quality.
- 4b-4 ran `pred solve` end-to-end via the new rule — overlaps with
the agentic feature tests review-pipeline already runs.
- 4b-1 (grep for the closed_loop test) is subsumed by Step 4's
existing checklist of required rule artefacts.
Restoring review-structural to its main version. Also removing the
Phase 4 prompt's mandatory-Step-4b clause from auto-pipeline.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Revert review-quality bullet to main version
The PR's edit added a Critical-severity rule for `[Rule]` PRs that
deferred to review-structural Step 4b-3 — now a dead link since that
section was reverted. Main's original bullet already captures the
intent: verify the extracted solution is optimal via brute-force on
both source and target.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Drop codex from auto-pipeline; use plain subagent dispatch
Removes the codex:codex-rescue dependency from both substantive-rewrite
(Step 1c-sub) and integration-gate-failure (Step 3) paths. Both now
dispatch a general-purpose subagent with the same JSON contract.
Wins:
- Step 1c-sub prompt drops from ~45 lines of nested codex-exec /
<<<BODY>>> / FUNDAMENTAL_FLAW sentinel escaping to a direct
subagent prompt with the issue body and check report inlined.
- Phase 3 failure path is consistent with the rest of the skill —
one subagent, one JSON return, orchestrator owns side effects.
No behaviour change to Step 2's stop-on-failure stance (run-pipeline
still moves the card to OnHold itself; orchestrator just halts).
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Drop batch-mode language from auto-pipeline Step 3 rationale
The skill is scoped to one issue at a time; batching is an external
concern. Step 3's rationale only needs to justify why catching
workspace-wide breakage locally beats waiting for CI.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Render canonical examples in paper for 13 batch-added rules
Adds `load-example` + `example: true` + `example-caption` + `extra:`
(pred-commands + witness summary) to the paper entries that previously
shipped without a rendered example, matching the existing `mvc_mis`
pattern. Brings the 13 outstanding rules in PR #1067 in line with the
already-rendered #363, #848, and #995.
Rules updated:
- DecisionMinimumVertexCover -> ComparativeContainment (#385)
- OptimalLinearArrangement -> SequencingToMinimizeWeightedCompletionTime (#472)
- Numerical3DimensionalMatching -> NumericalMatchingWithTargetSums (#827)
- MinimumCoveringByCliques -> MinimumIntersectionGraphBasis (#848 - was using older inline style)
- ThreeDimensionalMatching -> ThreeMatroidIntersection (#857, resolves sibling-inconsistency)
- MaximumCoKPlex -> ILP (#1016, i32 variant)
- MaximumCommonEdgeSubgraph -> ILP (#1019)
- MaximumEdgeWeightedKClique -> ILP (#1021, i32 variant)
- HighlyConnectedDeletion -> ILP (#1023)
- EulerianPath -> ILP (#1025)
- MinimumCostMaximumFlow -> MinimumCostCirculation (#1031)
- ClosestString -> ILP (#1034)
- ClosestSubstring -> ILP (#1035)
Verified: `make paper` compiles cleanly.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add rule: MinimumMaximalMatching -> MaximumAchromaticNumber (#846)
Classical Yannakakis-Gavril (1980) reduction establishing NP-completeness
of Achromatic Number (G&J GT5): for bipartite G, ach(complement(G)) =
|V| - mm(G). Adds BipartiteGraph variant of MinimumMaximalMatching as a
prerequisite, the complement-graph reduction with the inverse coloring ->
maximal-matching extractor, a closed-loop test plus identity tests on
several bipartite instances, the canonical P4 example (acknowledged
check-issue warning that the P4 canonical example has only one
suboptimal maximal matching; kept for tutorial clarity), and the matching
paper entry under docs/paper/reductions.typ.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add rule: MinimumMaximalMatching -> MinimumMatrixDomination (#847)
* Add rule: ExactCoverBy3Sets -> BoundedDiameterSpanningTree (#913)
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Fix nits: MinimumMaximalMatching -> MaximumAchromaticNumber (#846)
Address three review nits on commit 18268671:
1. Canonical example richness: swap the path P4 canonical example for a
"T-tree" on 5 vertices (spider v0-v1-v2-v3 with extra leaf v1-v4),
which exposes two strictly suboptimal maximal matchings besides the
minimum (mm = 1 vs. two size-2 maximal matchings), comfortably
passing the >=2-suboptimals rule-of-thumb. Update the canonical
builder, the paper worked example, and the closed-loop test to match.
2. extract_solution: replace the per-call HashMap rebuild with a single
pass over source_edges that checks whether each edge's endpoints
share a color. For bipartite G all color classes have size <= 2,
so this is equivalent and avoids any auxiliary allocation.
3. Unit test imports: drop the catch-all "use super::*" in favour of an
explicit "use" list mirroring the MVC->MIS reference test.
cargo test rules::minimummaximalmatching_maximumachromaticnumber: 5
passed (closed-loop, complement structure, known coloring, suboptimal
recovery, identity); make paper builds cleanly.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Fix nits: MinimumMaximalMatching -> MinimumMatrixDomination (#847)
* Fix nits: ExactCoverBy3Sets -> BoundedDiameterSpanningTree (#913)
- Add `q()` helper on ExactCoverBy3Sets and use it in the rule and tests
instead of recomputing `universe_size / 3`.
- Add a `debug_assert!` in `reduce_to` confirming that root-to-set edges
occupy indices 2..2+m, so a future reordering will surface a failure
in `extract_solution`.
- Simplify the `no_instance` test: drop the duplicate assertion and the
`unwrap_or_default` fallback; assert directly that `find_witness` is
`None` and that the brute-force aggregate is `Or(false)` for an
infeasible Or-valued target.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Fix nit: clarify invalid_source_solution intent (#848)
* Fix nits: HighlyConnectedDeletion -> ILP debug_assert guards (#1023)
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Fix nit: EulerianPath -> ILP extract_solution debug_assert (#1025)
* Fix nit: MaximumCoKPlex bound_k load-time validation (#1015)
* Fix nit: drop unused total_selected_vertices accumulator (#1026)
* Fix nit: correct canonical-example route comment (#1029)
* Add Planar3Satisfiability -> MinimumGeometricConnectedDominatingSet rule (#377)
Implements Lichtenstein 1982 §6 Theorem 5: NP-hardness of Minimum
Geometric Connected Dominating Set via Planar 3-SAT.
Construction:
- Phase A bipolarization via Lemma 1: introduce m_i copies per variable
with cycle implication clauses forcing all copies equal; rewrite each
source clause to use the per-occurrence copy. The bipolar formula B'
has Sigma_i m_i = 3m copy variables and m_b = 4m clauses.
- Phase B geometric embedding: emit per-copy-variable structures (top
and bottom column rounds plus square forcers), a ground spine
connecting them, and per-clause tripods. All points at radius = 1.
- Bound K = NV + NC + NG + m_b per Lichtenstein p. 339.
- Trivial corner case: num_clauses == 0 emits a 1-point target with K = 1.
Closed-loop test on the trivial m = 0 case (brute-force solvable);
structural tests verify radius, num_points overhead bound, K formula on
non-trivial instances. Full round-trip solve on non-trivial instances
requires a future MinimumGeometricConnectedDominatingSet -> ILP rule.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add closed-loop and structural tests for Planar3SAT -> GCD rule (#377)
Forgotten in the previous commit: the unit test file linked via
#[cfg(test)] #[path = ...] from the rule module. Without it, the rule
compiles but has no tests.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add canonical example for Planar3Satisfiability -> MinimumGeometricConnectedDominatingSet (#377)
* Fix fmt drift in minimummaximalmatching_minimummatrixdomination.rs
* Add reduction-rule block for Planar3SAT -> GCD in paper (#377)
* Add MaximumContactMapOverlap -> ILP rule (#1044)
Direct ILP rendering of the Andonov-Malod-Dognin-Yanev / Xie-Sahinidis
polyhedral formulation: binary x_(i,j) match variables, partial-injection
row/column constraints, order-preservation (no-crossing, no-equal-image)
constraints, and binary y_(i,k,j,l) contact-preservation variables linked
via y <= x_(i,j) and y <= x_(k,l). Objective: maximize sum of y.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add closed-loop tests for MaximumContactMapOverlap -> ILP (#1044)
Six unit tests covering:
- ILP structure: variable + constraint counts and Maximize sense
- closed-loop on the canonical issue instance (objective = 2)
- trivial no-contacts instance
- brute-force vs ILP optimum
- order-preservation rejection of crossing alignments
- extract_solution encoding (j -> j+1, unmatched -> 0)
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add reduction-rule block for MaximumContactMapOverlap -> ILP (#1044)
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Fix clippy + fmt nits in MaximumContactMapOverlap -> ILP tests (#1044)
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add KColoring -> BicliqueCover rule (#1058)
Self-contained gadget construction that maps a `KColoring(G, q)` instance
to a `BicliqueCover` instance on `4n` vertices with rank `n + q`. Each
source vertex `v` contributes diagonal/guard/compat edges; guard-anchor
edges force `n` bicliques to be spent on guards, leaving at most `q`
bicliques to encode color classes under the sub-biclique semantics.
Wires up `ReduceTo<BicliqueCover>` for `KColoring<KN, SimpleGraph>`,
registers the module in `src/rules/mod.rs`, and adds a canonical example
spec (P_2 with q=2) for the example-db.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add closed-loop and structure tests for KColoring -> BicliqueCover (#1058)
Nine tests covering:
- Closed-loop brute force on the trivial n=1, q=1 instance (8 binary vars).
- Structural checks of `num_vertices = 4n`, `rank = n + q`, and the exact
edge formula `2 n (n-1) - 4 m + 3 n` on a path and on K_4.
- Explicit edge enumeration for n=2 P_2.
- NO-instance check: K_4 with q=3 has no proper coloring.
- Forward-witness construction on P_3, C_4, K_3: verifies the guard +
color biclique cover is valid and that `extract_solution` recovers a
proper q-coloring.
- Adjacent-grouping rejection: confirms a witness merging adjacent source
vertices into one color biclique fails the sub-biclique check.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add reduction-rule block for KColoring -> BicliqueCover (#1058)
Adds the paper entry next to the existing KColoring -> Clustering rule,
summarizing the gadget construction (diagonal, compatibility, guard-anchor,
guard-compat edges), the bidirectional correctness argument, the edge
count formula `2 n (n-1) - 4 m + 3 n`, and the diagonal-biclique solution
extraction.
References Karp 1972, Garey-Johnson 1979, Orlin 1977 as background.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Fix clippy dead-code on forward_witness helper (#1058)
The forward_witness helper in src/rules/kcoloring_bicliquecover.rs was
gated with cfg(any(test, feature = "example-db")), but its only caller
(canonical_rule_example_specs) is gated with cfg(feature = "example-db").
Under cfg(test) without the example-db feature, the function was compiled
but unused, tripping clippy's dead-code lint.
Tighten the gate to cfg(feature = "example-db") to match its caller. The
test file maintains its own build_forward_witness copy, so test coverage
is unaffected.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add KSatisfiability/K3 -> BicliqueCover rule (#1057)
Implement the Chandran-Issac-Karrenbauer (IPEC 2016, Theorem 6) polynomial
reduction from 3-SAT to BicliqueCover with logarithmic rank. The reduction
normalizes the source formula (split each x_i into t_i, f_i with exactly-one
clauses; pad to n = 2^ell normalized variables) and then assembles a bipartite
gadget with crown H_n, clause matchings P_i, domino gadgets S_j, guard Q, and
forcing matching Y. Solution extraction identifies the biclique B_1 covering
s_{1,1}^u s_{1,1}^v (skipping Y-touching free-edge bicliques) and reads off
the normalized assignment via h_i^u in B_1, then maps back to source variables.
Includes a canonical rule example with a hand-built forward witness on the
smallest case (1 source variable, 1 source clause, rank 18). Free-edge
biclique enumeration follows Lemma 16 (H-S, P-P, P-Q, H-P, S_1-P sets).
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add closed-loop and structure tests for KSAT/K3 -> BicliqueCover (#1057)
Adds seven unit tests covering the new reduction:
- Structural sizes for the smallest source (n=2, ell=1, m=3, rank=18).
- Structural sizes for the four-variable example from the issue body
(n=8, ell=3, m=10, rank=26) — the post-normalization rank is higher
than the issue's 22 because we faithfully emit the exactly-one clauses.
- Construction termination on a UNSAT formula.
- extract_solution reading B_1 (positive-literal h-vertex) from a hand-built
partial witness.
- extract_solution skipping Y-touching free-edge bicliques.
- Two-variable instance constructs without index-out-of-bounds.
- Full closed-loop on the smallest source using the canonical forward
witness from the example-db builder (gated on the example-db feature).
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add paper entry + BibTeX for KSAT/K3 -> BicliqueCover (#1057)
- Insert reduction-rule("KSatisfiability", "BicliqueCover", ...) block into
docs/paper/reductions.typ with normalization, construction, correctness,
and solution-extraction sections.
- Add chandran_et_al:LIPIcs.IPEC.2016.11 BibTeX entry to references.bib.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Fix Phase 3 nits in KSatisfiability/K3 -> BicliqueCover (#1057)
- Gate `use crate::traits::Problem;` behind `cfg(feature = "example-db")`
in the unit test, matching the feature gate on the only test that
uses `evaluate` (clippy `--features ilp-highs` flagged it as unused).
- Fix Typst syntax error in the reduction-rule proof: stray `$` inside
`$x_i = ($h_i^u in B_1)$` produced an unclosed delimiter; corrected to
`$x_i = (h_i^u in B_1)$` so `make paper` compiles.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add ShortestCommonSuperstring model (#413)
Implements ShortestCommonSuperstring (Garey & Johnson SR9, P157) as a
minimization problem: given an alphabet Sigma and a set R of strings,
find a shortest w in Sigma^* that contains every r in R as a contiguous
substring. Uses Min<usize> value, fixed-length configuration with a
sentinel padding symbol (mirroring sibling ShortestCommonSupersequence),
and max_length derived in new() as the sum of input string lengths.
Includes problem-def paper entry with CeTZ embedding diagram, canonical
example_db instance, and unit tests covering the three issue examples
(optima 9, 8, 7; the small one verified by brute force).
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add QuadraticProgramming model (#528)
Implements the bounded integer variant of Quadratic Programming (G&J MP2):
minimize sum_i (c_i*y_i^2 + d_i*y_i) over y in {-K, ..., K}^m subject to
linear inequality constraints x . y <= b. NP-hardness follows from Sahni
(1974) PARTITION -> QP, whose construction lands on {0,1}^m.
- Value = Min<f64>; infeasible configs return Min(None)
- dims = vec![2*bound + 1; num_vars] with y_i = config_i - bound
- Reuses LinearConstraint from the ILP model
- Canonical example reproduces the Sahni PARTITION encoding for a=(1,1,2):
optimum y=(1,1,0) with objective 0
- Paper entry + Vavasis (1990) NP-membership reference
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add Partition -> SumOfSquaresPartition rule (#393)
Witness reduction specialising Garey & Johnson SP19 to K = 2: copy element
sizes verbatim into a SumOfSquaresPartition with two groups. Source YES iff
the optimal target witness is a balanced split, which Partition::evaluate
accepts via identity solution extraction. Singleton sources take a sentinel
path (target on two unit elements) that returns the all-zero source
configuration, correctly classified as NO.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add MaxCut -> MinimumMatrixCover rule (#925)
Implements the canonical Garey & Johnson MS13 reduction: given a MaxCut
instance (G, w) on SimpleGraph with nonnegative i32 edge weights, take
the weighted adjacency matrix A as the MinimumMatrixCover instance. The
identity sum_{i,j} a_ij f(i) f(j) = 2W - 4 * cut(S) makes MaxCut and
MinimumMatrixCover equivalent up to the constant 2W, and the binary
encoding (config[i] = 1 iff i in S iff f(i) = +1) makes solution
extraction the identity map.
- Source variant: MaxCut/SimpleGraph/i32 with nonneg precondition; the
reduction panics on any negative edge weight, mirroring the model's
nonnegative-matrix invariant.
- Overhead: num_rows = num_vertices.
- Closed-loop tests cover C_4 (unit weights), weighted P_3, K_3, plus
the algebraic identity check on every sign assignment and a
negative-weight precondition test.
- Canonical example_db builder uses C_4 with unit weights.
- Paper entry under docs/paper/reductions.typ with construction,
correctness proof, precondition note, and a worked C_4 walk-through.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* Add PrizeCollectingSteinerForest -> SteinerTree rule (#1027)
* Add ThreeDimensionalMatching -> MinimumWeightDecoding rule (#916)
Berlekamp-McEliece-van Tilborg (1978) / G&J MS7 construction: each triple
becomes a column of a 3q x m binary parity-check matrix with all-ones
syndrome; minimum weight codeword = q iff a perfect 3DM matching exists.
Witness reduction (Or -> Min<usize>) with a 1x1 sentinel for q=0 or empty
triple set. Tests cap at q=3, 5 triples (2^5 target search space).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* Add Decision<OptimalLinearArrangement> -> ConsecutiveOnesMatrixAugmentation rule (#434)
Register the Decision<OptimalLinearArrangement> variant (prerequisite) and
implement the reduction to ConsecutiveOnesMatrixAugmentation via the
edge-vertex incidence matrix with augmentation bound k - |E|, including the
m=0 always-YES sentinel and the k<m genuine-NO cyclic-overlap sentinel.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* Remove unused Solver import in PCSF->SteinerTree example builder (#1027)
Surfaced under --features example-db; would fail clippy -D warnings.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* Add Decision<OptimalLinearArrangement> aggregate-edge example + bib cleanup (#434)
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* Apply rustfmt to OLA->C1MA rule files (#434)
Fixes inline-comment spacing flagged by cargo fmt --check.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* Replace deprecated sect with inter in PCSF->SteinerTree proof (#1027)
Typst deprecated the `sect` set-intersection operator in favor of `inter`;
silences the only remaining make paper warning.
Co-Authored-By: Claude Opus 4.7 (1M contex…1 parent 7068560 commit c40e943
103 files changed
Lines changed: 17835 additions & 144 deletions
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