Fix #216: Add HamiltonianCircuit model

docs/paper/reductions.typ

@@ -66,6 +66,7 @@
   "MinimumVertexCover": [Minimum Vertex Cover],
   "MaxCut": [Max-Cut],
   "GraphPartitioning": [Graph Partitioning],
+  "HamiltonianCircuit": [Hamiltonian Circuit],
   "BiconnectivityAugmentation": [Biconnectivity Augmentation],
   "HamiltonianPath": [Hamiltonian Path],
   "UndirectedTwoCommodityIntegralFlow": [Undirected Two-Commodity Integral Flow],
@@ -595,6 +596,65 @@ Biconnectivity augmentation is a classical network-design problem: add backup li
   caption: [Biconnectivity Augmentation on a 6-vertex path with $B = 4$. Existing edges are black; green arcs show the selected augmentation $F'$ (total weight 4); dashed gray arcs are unselected candidates. The resulting graph $G' = (V, E union F')$ is biconnected.],
 ) <fig:biconnectivity-augmentation>
 ]
+#{
+  let x = load-model-example("HamiltonianCircuit")
+  let nv = graph-num-vertices(x.instance)
+  let ne = graph-num-edges(x.instance)
+  let edges = x.instance.graph.inner.edges.map(e => (e.at(0), e.at(1)))
+  let sol = x.optimal.at(0)
+  let circuit = sol.config
+  // Build circuit edges from consecutive vertices (including wrap-around)
+  let circuit-edges = range(circuit.len()).map(i => (circuit.at(i), circuit.at(calc.rem(i + 1, circuit.len()))))
+  [
+    #problem-def("HamiltonianCircuit")[
+      *Instance:* An undirected graph $G = (V, E)$.
+
+      *Question:* Does $G$ contain a _Hamiltonian circuit_ --- a closed path that visits every vertex exactly once?
+    ][
+      The Hamiltonian Circuit problem is one of Karp's original 21 NP-complete problems @karp1972, and is listed as GT37 in Garey & Johnson @garey1979.
+      It is closely related to the Traveling Salesman Problem: while TSP seeks to minimize the total weight of a Hamiltonian cycle on a weighted complete graph, the Hamiltonian Circuit problem simply asks whether _any_ such cycle exists on a general (unweighted) graph.
+
+      A configuration is a permutation $pi$ of the vertices, interpreted as the order in which they are visited.
+      The circuit is valid when every consecutive pair $(pi(i), pi(i+1 mod n))$ is an edge in $G$.
+
+      *Algorithms.*
+      The classical Held--Karp dynamic programming algorithm @heldkarp1962 solves the problem in $O(n^2 dot 2^n)$ time and $O(n dot 2^n)$ space.
+      Björklund's randomized "Determinant Sums" algorithm achieves $O^*(1.657^n)$ time for general graphs and $O^*(sqrt(2)^n)$ for bipartite graphs @bjorklund2014.
+
+      *Example.* Consider the triangular prism graph $G$ on #nv vertices with #ne edges. The permutation $[#circuit.map(v => str(v)).join(", ")]$ forms a Hamiltonian circuit: each consecutive pair #circuit-edges.map(((u, v)) => $(#u, #v)$).join($,$) is an edge of $G$, and the path returns to the start.
+
+      #figure({
+        let blue = graph-colors.at(0)
+        let gray = luma(200)
+        canvas(length: 1cm, {
+          import draw: *
+          // Triangular prism: outer triangle + inner triangle
+          let r-out = 1.8
+          let r-in = 0.9
+          let verts = range(3).map(k => {
+            let angle = 90deg - k * 120deg
+            (calc.cos(angle) * r-out, calc.sin(angle) * r-out)
+          }) + range(3).map(k => {
+            let angle = 90deg - k * 120deg
+            (calc.cos(angle) * r-in, calc.sin(angle) * r-in)
+          })
+          for (u, v) in edges {
+            let on-circuit = circuit-edges.any(e => (e.at(0) == u and e.at(1) == v) or (e.at(0) == v and e.at(1) == u))
+            g-edge(verts.at(u), verts.at(v), stroke: if on-circuit { 2pt + blue } else { 1pt + gray })
+          }
+          for (k, pos) in verts.enumerate() {
+            g-node(pos, name: "v" + str(k),
+              fill: blue,
+              label: text(fill: white)[$v_#k$])
+          }
+        })
+      },
+      caption: [Hamiltonian Circuit in the triangular prism graph. Blue edges show the circuit $#circuit.map(v => $v_#v$).join($arrow$) arrow v_#(circuit.at(0))$.],
+      ) <fig:hamiltonian-circuit>
+    ]
+  ]
+}
+
 
 #problem-def("BoundedComponentSpanningForest")[
   Given an undirected graph $G = (V, E)$ with vertex weights $w: V -> ZZ_(gt.eq 0)$, a positive integer $K <= |V|$, and a positive bound $B$, determine whether there exists a partition of $V$ into $t$ non-empty sets $V_1, dots, V_t$ with $1 <= t <= K$ such that each induced subgraph $G[V_i]$ is connected and each part satisfies $sum_(v in V_i) w(v) <= B$.

docs/paper/references.bib

@@ -311,6 +311,17 @@ @inproceedings{zamir2021
   doi       = {10.4230/LIPIcs.ICALP.2021.113}
 }
 
+@article{bjorklund2014,
+  author  = {Andreas Bj\"{o}rklund},
+  title   = {Determinant Sums for Undirected {H}amiltonicity},
+  journal = {SIAM Journal on Computing},
+  volume  = {43},
+  number  = {1},
+  pages   = {280--299},
+  year    = {2014},
+  doi     = {10.1137/110839229}
+}
+
 @article{bjorklund2009,
   author  = {Andreas Bj\"{o}rklund and Thore Husfeldt and Mikko Koivisto},
   title   = {Set Partitioning via Inclusion-Exclusion},
@@ -322,17 +333,6 @@ @article{bjorklund2009
   doi     = {10.1137/070683933}
 }
 
-@article{bjorklund2014,
-  author    = {Andreas Bj{\"o}rklund},
-  title     = {Determinant Sums for Undirected Hamiltonicity},
-  journal   = {SIAM Journal on Computing},
-  volume    = {43},
-  number    = {1},
-  pages     = {280--299},
-  year      = {2014},
-  doi       = {10.1137/110839229},
-}
-
 @article{aspvall1979,
   author  = {Bengt Aspvall and Michael F. Plass and Robert Endre Tarjan},
   title   = {A Linear-Time Algorithm for Testing the Truth of Certain Quantified Boolean Formulas},

problemreductions-cli/src/cli.rs

@@ -225,6 +225,7 @@ Flags by problem type:
   MinimumMultiwayCut              --graph, --terminals, --edge-weights
   PartitionIntoTriangles          --graph
   GraphPartitioning               --graph
+  HamiltonianCircuit, HC          --graph
   BoundedComponentSpanningForest  --graph, --weights, --k, --bound
   UndirectedTwoCommodityIntegralFlow --graph, --capacities, --source-1, --sink-1, --source-2, --sink-2, --requirement-1, --requirement-2
   IsomorphicSpanningTree          --graph, --tree

problemreductions-cli/src/commands/create.rs

@@ -9,8 +9,8 @@ use anyhow::{bail, Context, Result};
 use problemreductions::export::{ModelExample, ProblemRef, ProblemSide, RuleExample};
 use problemreductions::models::algebraic::{ClosestVectorProblem, BMF};
 use problemreductions::models::graph::{
-    GraphPartitioning, HamiltonianPath, LengthBoundedDisjointPaths, MinimumMultiwayCut,
-    MultipleChoiceBranching, SteinerTree, StrongConnectivityAugmentation,
+    GraphPartitioning, HamiltonianCircuit, HamiltonianPath, LengthBoundedDisjointPaths,
+    MinimumMultiwayCut, MultipleChoiceBranching, SteinerTree, StrongConnectivityAugmentation,
 };
 use problemreductions::models::misc::{
     BinPacking, FlowShopScheduling, LongestCommonSubsequence, MinimumTardinessSequencing,
@@ -299,6 +299,7 @@ fn example_for(canonical: &str, graph_type: Option<&str>) -> &'static str {
         "QUBO" => "--matrix \"1,0.5;0.5,2\"",
         "SpinGlass" => "--graph 0-1,1-2 --couplings 1,1",
         "KColoring" => "--graph 0-1,1-2,2-0 --k 3",
+        "HamiltonianCircuit" => "--graph 0-1,1-2,2-3,3-0",
         "MinimumSumMulticenter" => {
             "--graph 0-1,1-2,2-3 --weights 1,1,1,1 --edge-weights 1,1,1 --k 2"
         }
@@ -634,6 +635,19 @@ pub fn create(args: &CreateArgs, out: &OutputConfig) -> Result<()> {
             )
         }
 
+        // Hamiltonian Circuit (graph only, no weights)
+        "HamiltonianCircuit" => {
+            let (graph, _) = parse_graph(args).map_err(|e| {
+                anyhow::anyhow!(
+                    "{e}\n\nUsage: pred create HamiltonianCircuit --graph 0-1,1-2,2-3,3-0"
+                )
+            })?;
+            (
+                ser(HamiltonianCircuit::new(graph))?,
+                resolved_variant.clone(),
+            )
+        }
+
         // Biconnectivity augmentation
         "BiconnectivityAugmentation" => {
             let (graph, _) = parse_graph(args).map_err(|e| {
@@ -3068,6 +3082,17 @@ fn create_random(
             (ser(GraphPartitioning::new(graph))?, variant)
         }
 
+        // Hamiltonian Circuit (graph only, no weights)
+        "HamiltonianCircuit" => {
+            let edge_prob = args.edge_prob.unwrap_or(0.5);
+            if !(0.0..=1.0).contains(&edge_prob) {
+                bail!("--edge-prob must be between 0.0 and 1.0");
+            }
+            let graph = util::create_random_graph(num_vertices, edge_prob, args.seed);
+            let variant = variant_map(&[("graph", "SimpleGraph")]);
+            (ser(HamiltonianCircuit::new(graph))?, variant)
+        }
+
         // HamiltonianPath (graph only, no weights)
         "HamiltonianPath" => {
             let edge_prob = args.edge_prob.unwrap_or(0.5);
@@ -3219,7 +3244,7 @@ fn create_random(
             "Random generation is not supported for {canonical}. \
              Supported: graph-based problems (MIS, MVC, MaxCut, MaxClique, \
              MaximumMatching, MinimumDominatingSet, SpinGlass, KColoring, TravelingSalesman, \
-             SteinerTree, OptimalLinearArrangement, HamiltonianPath)"
+             HamiltonianCircuit, SteinerTree, OptimalLinearArrangement, HamiltonianPath)"
         ),
     };
 

src/example_db/fixtures/examples.json

@@ -12,6 +12,7 @@
     {"problem":"DirectedTwoCommodityIntegralFlow","variant":{},"instance":{"capacities":[1,1,1,1,1,1,1,1],"graph":{"inner":{"edge_property":"directed","edges":[[0,2,null],[0,3,null],[1,2,null],[1,3,null],[2,4,null],[2,5,null],[3,4,null],[3,5,null]],"node_holes":[],"nodes":[null,null,null,null,null,null]}},"requirement_1":1,"requirement_2":1,"sink_1":4,"sink_2":5,"source_1":0,"source_2":1},"samples":[{"config":[1,0,0,0,1,0,0,0,0,0,0,1,0,0,0,1],"metric":true}],"optimal":[{"config":[0,0,0,1,0,0,1,0,0,0,1,0,0,1,0,0],"metric":true},{"config":[0,0,0,1,0,0,1,0,0,1,0,0,0,0,0,1],"metric":true},{"config":[0,0,0,1,0,0,1,0,0,1,1,0,0,1,0,1],"metric":true},{"config":[0,0,0,1,0,0,1,0,0,1,1,0,1,0,0,1],"metric":true},{"config":[0,0,0,1,0,0,1,0,1,0,0,0,0,1,0,0],"metric":true},{"config":[0,0,0,1,0,0,1,0,1,0,1,0,1,1,0,0],"metric":true},{"config":[0,0,0,1,0,0,1,0,1,1,0,0,0,1,0,1],"metric":true},{"config":[0,0,0,1,0,0,1,0,1,1,0,0,1,0,0,1],"metric":true},{"config":[0,0,0,1,0,0,1,0,1,1,1,0,1,1,0,1],"metric":true},{"config":[0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,1],"metric":true},{"config":[0,0,1,0,1,0,0,0,0,1,0,0,0,0,0,1],"metric":true},{"config":[0,0,1,0,1,0,0,0,0,1,0,1,0,0,1,1],"metric":true},{"config":[0,0,1,0,1,0,0,0,1,0,0,0,0,1,0,0],"metric":true},{"config":[0,0,1,0,1,0,0,0,1,0,0,1,0,1,0,1],"metric":true},{"config":[0,0,1,0,1,0,0,0,1,0,0,1,0,1,1,0],"metric":true},{"config":[0,0,1,0,1,0,0,0,1,1,0,0,0,1,0,1],"metric":true},{"config":[0,0,1,0,1,0,0,0,1,1,0,0,0,1,1,0],"metric":true},{"config":[0,0,1,0,1,0,0,0,1,1,0,1,0,1,1,1],"metric":true},{"config":[0,0,1,1,0,1,1,0,0,1,0,0,0,0,0,1],"metric":true},{"config":[0,0,1,1,0,1,1,0,1,1,0,0,1,0,0,1],"metric":true},{"config":[0,0,1,1,1,0,0,1,1,0,0,0,0,1,0,0],"metric":true},{"config":[0,0,1,1,1,0,0,1,1,1,0,0,0,1,1,0],"metric":true},{"config":[0,0,1,1,1,0,1,0,0,1,0,0,0,0,0,1],"metric":true},{"config":[0,0,1,1,1,0,1,0,1,0,0,0,0,1,0,0],"metric":true},{"config":[0,0,1,1,1,0,1,0,1,1,0,0,0,1,0,1],"metric":true},{"config":[0,1,0,0,0,0,1,0,0,0,0,1,0,0,0,1],"metric":true},{"config":[0,1,0,0,0,0,1,0,0,0,1,0,0,1,0,0],"metric":true},{"config":[0,1,0,0,0,0,1,0,0,0,1,1,0,1,0,1],"metric":true},{"config":[0,1,0,0,0,0,1,0,0,0,1,1,1,0,0,1],"metric":true},{"config":[0,1,0,0,0,0,1,0,1,0,0,0,0,1,0,0],"metric":true},{"config":[0,1,0,0,0,0,1,0,1,0,0,1,0,1,0,1],"metric":true},{"config":[0,1,0,0,0,0,1,0,1,0,0,1,1,0,0,1],"metric":true},{"config":[0,1,0,0,0,0,1,0,1,0,1,0,1,1,0,0],"metric":true},{"config":[0,1,0,0,0,0,1,0,1,0,1,1,1,1,0,1],"metric":true},{"config":[0,1,0,1,0,0,1,1,0,0,1,0,0,1,0,0],"metric":true},{"config":[0,1,0,1,0,0,1,1,1,0,0,0,0,1,0,0],"metric":true},{"config":[0,1,0,1,0,0,1,1,1,0,1,0,1,1,0,0],"metric":true},{"config":[0,1,1,0,0,1,1,0,0,0,0,1,0,0,0,1],"metric":true},{"config":[0,1,1,0,0,1,1,0,1,0,0,1,1,0,0,1],"metric":true},{"config":[0,1,1,0,1,0,0,1,1,0,0,0,0,1,0,0],"metric":true},{"config":[0,1,1,0,1,0,0,1,1,0,0,1,0,1,1,0],"metric":true},{"config":[0,1,1,0,1,0,1,0,0,0,0,1,0,0,0,1],"metric":true},{"config":[0,1,1,0,1,0,1,0,1,0,0,0,0,1,0,0],"metric":true},{"config":[0,1,1,0,1,0,1,0,1,0,0,1,0,1,0,1],"metric":true},{"config":[0,1,1,1,1,0,1,1,1,0,0,0,0,1,0,0],"metric":true},{"config":[1,0,0,0,1,0,0,0,0,0,0,1,0,0,0,1],"metric":true},{"config":[1,0,0,0,1,0,0,0,0,0,1,0,0,1,0,0],"metric":true},{"config":[1,0,0,0,1,0,0,0,0,0,1,1,0,1,0,1],"metric":true},{"config":[1,0,0,0,1,0,0,0,0,0,1,1,0,1,1,0],"metric":true},{"config":[1,0,0,0,1,0,0,0,0,1,0,0,0,0,0,1],"metric":true},{"config":[1,0,0,0,1,0,0,0,0,1,0,1,0,0,1,1],"metric":true},{"config":[1,0,0,0,1,0,0,0,0,1,1,0,0,1,0,1],"metric":true},{"config":[1,0,0,0,1,0,0,0,0,1,1,0,0,1,1,0],"metric":true},{"config":[1,0,0,0,1,0,0,0,0,1,1,1,0,1,1,1],"metric":true},{"config":[1,0,0,1,0,1,1,0,0,1,0,0,0,0,0,1],"metric":true},{"config":[1,0,0,1,0,1,1,0,0,1,1,0,1,0,0,1],"metric":true},{"config":[1,0,0,1,1,0,0,1,0,0,1,0,0,1,0,0],"metric":true},{"config":[1,0,0,1,1,0,0,1,0,1,1,0,0,1,1,0],"metric":true},{"config":[1,0,0,1,1,0,1,0,0,0,1,0,0,1,0,0],"metric":true},{"config":[1,0,0,1,1,0,1,0,0,1,0,0,0,0,0,1],"metric":true},{"config":[1,0,0,1,1,0,1,0,0,1,1,0,0,1,0,1],"metric":true},{"config":[1,0,1,0,1,1,0,0,0,0,0,1,0,0,0,1],"metric":true},{"config":[1,0,1,0,1,1,0,0,0,1,0,0,0,0,0,1],"metric":true},{"config":[1,0,1,0,1,1,0,0,0,1,0,1,0,0,1,1],"metric":true},{"config":[1,0,1,1,1,1,1,0,0,1,0,0,0,0,0,1],"metric":true},{"config":[1,1,0,0,0,1,1,0,0,0,0,1,0,0,0,1],"metric":true},{"config":[1,1,0,0,0,1,1,0,0,0,1,1,1,0,0,1],"metric":true},{"config":[1,1,0,0,1,0,0,1,0,0,1,0,0,1,0,0],"metric":true},{"config":[1,1,0,0,1,0,0,1,0,0,1,1,0,1,1,0],"metric":true},{"config":[1,1,0,0,1,0,1,0,0,0,0,1,0,0,0,1],"metric":true},{"config":[1,1,0,0,1,0,1,0,0,0,1,0,0,1,0,0],"metric":true},{"config":[1,1,0,0,1,0,1,0,0,0,1,1,0,1,0,1],"metric":true},{"config":[1,1,0,1,1,0,1,1,0,0,1,0,0,1,0,0],"metric":true},{"config":[1,1,1,0,1,1,1,0,0,0,0,1,0,0,0,1],"metric":true}]},
     {"problem":"ExactCoverBy3Sets","variant":{},"instance":{"subsets":[[0,1,2],[0,2,4],[3,4,5],[3,5,7],[6,7,8],[1,4,6],[2,5,8]],"universe_size":9},"samples":[{"config":[1,0,1,0,1,0,0],"metric":true}],"optimal":[{"config":[1,0,1,0,1,0,0],"metric":true}]},
     {"problem":"Factoring","variant":{},"instance":{"m":2,"n":3,"target":15},"samples":[{"config":[1,1,1,0,1],"metric":{"Valid":0}}],"optimal":[{"config":[1,1,1,0,1],"metric":{"Valid":0}}]},
+    {"problem":"HamiltonianCircuit","variant":{"graph":"SimpleGraph"},"instance":{"graph":{"inner":{"edge_property":"undirected","edges":[[0,1,null],[1,2,null],[2,0,null],[3,4,null],[4,5,null],[5,3,null],[0,3,null],[1,4,null],[2,5,null]],"node_holes":[],"nodes":[null,null,null,null,null,null]}}},"samples":[{"config":[0,1,2,5,4,3],"metric":true}],"optimal":[{"config":[0,1,2,5,4,3],"metric":true},{"config":[0,1,4,3,5,2],"metric":true},{"config":[0,2,1,4,5,3],"metric":true},{"config":[0,2,5,3,4,1],"metric":true},{"config":[0,3,4,5,2,1],"metric":true},{"config":[0,3,5,4,1,2],"metric":true},{"config":[1,0,2,5,3,4],"metric":true},{"config":[1,0,3,4,5,2],"metric":true},{"config":[1,2,0,3,5,4],"metric":true},{"config":[1,2,5,4,3,0],"metric":true},{"config":[1,4,3,5,2,0],"metric":true},{"config":[1,4,5,3,0,2],"metric":true},{"config":[2,0,1,4,3,5],"metric":true},{"config":[2,0,3,5,4,1],"metric":true},{"config":[2,1,0,3,4,5],"metric":true},{"config":[2,1,4,5,3,0],"metric":true},{"config":[2,5,3,4,1,0],"metric":true},{"config":[2,5,4,3,0,1],"metric":true},{"config":[3,0,1,2,5,4],"metric":true},{"config":[3,0,2,1,4,5],"metric":true},{"config":[3,4,1,0,2,5],"metric":true},{"config":[3,4,5,2,1,0],"metric":true},{"config":[3,5,2,0,1,4],"metric":true},{"config":[3,5,4,1,2,0],"metric":true},{"config":[4,1,0,2,5,3],"metric":true},{"config":[4,1,2,0,3,5],"metric":true},{"config":[4,3,0,1,2,5],"metric":true},{"config":[4,3,5,2,0,1],"metric":true},{"config":[4,5,2,1,0,3],"metric":true},{"config":[4,5,3,0,2,1],"metric":true},{"config":[5,2,0,1,4,3],"metric":true},{"config":[5,2,1,0,3,4],"metric":true},{"config":[5,3,0,2,1,4],"metric":true},{"config":[5,3,4,1,0,2],"metric":true},{"config":[5,4,1,2,0,3],"metric":true},{"config":[5,4,3,0,1,2],"metric":true}]},
     {"problem":"HamiltonianPath","variant":{"graph":"SimpleGraph"},"instance":{"graph":{"inner":{"edge_property":"undirected","edges":[[0,1,null],[0,2,null],[1,3,null],[2,3,null],[3,4,null],[3,5,null],[4,2,null],[5,1,null]],"node_holes":[],"nodes":[null,null,null,null,null,null]}}},"samples":[{"config":[0,2,4,3,1,5],"metric":true}],"optimal":[{"config":[0,1,5,3,2,4],"metric":true},{"config":[0,1,5,3,4,2],"metric":true},{"config":[0,2,4,3,1,5],"metric":true},{"config":[0,2,4,3,5,1],"metric":true},{"config":[1,0,2,4,3,5],"metric":true},{"config":[1,5,3,4,2,0],"metric":true},{"config":[2,0,1,5,3,4],"metric":true},{"config":[2,4,3,5,1,0],"metric":true},{"config":[3,4,2,0,1,5],"metric":true},{"config":[3,5,1,0,2,4],"metric":true},{"config":[4,2,0,1,3,5],"metric":true},{"config":[4,2,0,1,5,3],"metric":true},{"config":[4,2,3,5,1,0],"metric":true},{"config":[4,3,2,0,1,5],"metric":true},{"config":[4,3,5,1,0,2],"metric":true},{"config":[5,1,0,2,3,4],"metric":true},{"config":[5,1,0,2,4,3],"metric":true},{"config":[5,1,3,4,2,0],"metric":true},{"config":[5,3,1,0,2,4],"metric":true},{"config":[5,3,4,2,0,1],"metric":true}]},
     {"problem":"ILP","variant":{"variable":"i32"},"instance":{"constraints":[{"cmp":"Le","rhs":5.0,"terms":[[0,1.0],[1,1.0]]},{"cmp":"Le","rhs":28.0,"terms":[[0,4.0],[1,7.0]]}],"num_vars":2,"objective":[[0,-5.0],[1,-6.0]],"sense":"Minimize"},"samples":[{"config":[0,4],"metric":{"Valid":-24.0}}],"optimal":[{"config":[3,2],"metric":{"Valid":-27.0}}]},
     {"problem":"IsomorphicSpanningTree","variant":{},"instance":{"graph":{"inner":{"edge_property":"undirected","edges":[[0,1,null],[0,2,null],[0,3,null],[1,2,null],[1,3,null],[2,3,null]],"node_holes":[],"nodes":[null,null,null,null]}},"tree":{"inner":{"edge_property":"undirected","edges":[[0,1,null],[0,2,null],[0,3,null]],"node_holes":[],"nodes":[null,null,null,null]}}},"samples":[{"config":[0,1,2,3],"metric":true}],"optimal":[{"config":[0,1,2,3],"metric":true},{"config":[0,1,3,2],"metric":true},{"config":[0,2,1,3],"metric":true},{"config":[0,2,3,1],"metric":true},{"config":[0,3,1,2],"metric":true},{"config":[0,3,2,1],"metric":true},{"config":[1,0,2,3],"metric":true},{"config":[1,0,3,2],"metric":true},{"config":[1,2,0,3],"metric":true},{"config":[1,2,3,0],"metric":true},{"config":[1,3,0,2],"metric":true},{"config":[1,3,2,0],"metric":true},{"config":[2,0,1,3],"metric":true},{"config":[2,0,3,1],"metric":true},{"config":[2,1,0,3],"metric":true},{"config":[2,1,3,0],"metric":true},{"config":[2,3,0,1],"metric":true},{"config":[2,3,1,0],"metric":true},{"config":[3,0,1,2],"metric":true},{"config":[3,0,2,1],"metric":true},{"config":[3,1,0,2],"metric":true},{"config":[3,1,2,0],"metric":true},{"config":[3,2,0,1],"metric":true},{"config":[3,2,1,0],"metric":true}]},

src/lib.rs

@@ -47,8 +47,8 @@ pub mod prelude {
     pub use crate::models::graph::{
         BalancedCompleteBipartiteSubgraph, BicliqueCover, BiconnectivityAugmentation,
         BoundedComponentSpanningForest, DirectedTwoCommodityIntegralFlow, GraphPartitioning,
-        HamiltonianPath, IsomorphicSpanningTree, LengthBoundedDisjointPaths, SpinGlass,
-        SteinerTree, StrongConnectivityAugmentation, SubgraphIsomorphism,
+        HamiltonianCircuit, HamiltonianPath, IsomorphicSpanningTree, LengthBoundedDisjointPaths,
+        SpinGlass, SteinerTree, StrongConnectivityAugmentation, SubgraphIsomorphism,
     };
     pub use crate::models::graph::{
         KColoring, MaxCut, MaximalIS, MaximumClique, MaximumIndependentSet, MaximumMatching,