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update rustdoc
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‎src/lib.rs‎

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//! # Problem Reductions
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//!
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//! A Rust library for reducing NP-hard problems.
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//! NP-hard problem definitions and reductions.
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//! See the [user guide](https://codingthrust.github.io/problem-reductions/) for tutorials and examples.
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//!
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//! This library provides implementations of various NP-hard computational problems
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//! and reduction rules between them. It is designed for algorithm research,
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//! education, and quantum optimization studies.
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//! ## API Overview
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//!
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//! ## Features
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//! | Module | Purpose |
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//! |--------|---------|
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//! | [`models`] | Problem types — [`graph`](models::graph), [`satisfiability`](models::satisfiability), [`set`](models::set), [`optimization`](models::optimization), [`specialized`](models::specialized) |
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//! | [`rules`] | Reduction rules, [`ReductionGraph`](rules::ReductionGraph) for path search |
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//! | [`solvers`] | [`BruteForce`] and [`ILPSolver`](solvers::ILPSolver) |
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//! | [`topology`] | Graph types — [`SimpleGraph`](topology::SimpleGraph), [`HyperGraph`](topology::HyperGraph), [`UnitDiskGraph`](topology::UnitDiskGraph), etc. |
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//! | [`traits`] | Core traits — [`Problem`], [`OptimizationProblem`], [`SatisfactionProblem`] |
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//! | [`types`] | [`SolutionSize`], [`Direction`], [`ProblemSize`], [`WeightElement`] |
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//! | [`variant`] | Variant parameter system for problem type parameterization |
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//!
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//! - **Problem Definitions**: Implementations of 21+ NP-hard problems
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//! - **Reduction Rules**: Transform problems into equivalent problems
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//! - **Solvers**: Brute-force solver for testing and verification
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//! - **Validation**: Utilities to verify solution validity
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//!
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//! ## Example
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//!
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//! ```rust
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//! use problemreductions::prelude::*;
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//! use problemreductions::models::graph::MaximumIndependentSet;
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//! use problemreductions::topology::SimpleGraph;
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//!
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//! // Create an Independent Set problem on a triangle graph
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//! let problem = MaximumIndependentSet::new(SimpleGraph::new(3, vec![(0, 1), (1, 2), (0, 2)]), vec![1i32; 3]);
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//!
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//! // Solve with brute force
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//! let solver = BruteForce::new();
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//! let solution = solver.find_best(&problem).unwrap();
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//!
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//! // Maximum independent set in a triangle has size 1
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//! assert_eq!(solution.iter().sum::<usize>(), 1);
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//! ```
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//!
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//! ## Problem Categories
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//!
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//! ### Satisfiability
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//! - SAT: Boolean satisfiability with CNF clauses
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//! - K-SAT: SAT restricted to k-literal clauses
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//! - CircuitSAT: Boolean circuit satisfiability
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//! - Factoring: Integer factorization
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//!
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//! ### Graph Problems
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//! - MaximumIndependentSet: Maximum weight independent set
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//! - MaximalIS: Maximal independent set
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//! - MinimumVertexCover: Minimum weight vertex cover
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//! - MinimumDominatingSet: Minimum dominating set
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//! - MaximumClique: Maximum weight clique
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//! - MaxCut: Maximum cut on weighted graphs
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//! - MaximumMatching: Maximum weight matching
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//! - KColoring: K-vertex coloring
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//! - TravelingSalesman: Minimum weight Hamiltonian cycle
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//!
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//! ### Set Problems
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//! - MinimumSetCovering: Minimum weight set cover
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//! - MaximumSetPacking: Maximum weight set packing
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//!
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//! ### Optimization Problems
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//! - SpinGlass: Ising model Hamiltonian
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//! - QUBO: Quadratic unconstrained binary optimization
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//! - ILP: Integer linear programming
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//!
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//! ### Specialized Problems
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//! - PaintShop: Minimize color switches
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//! - BicliqueCover: Biclique cover on bipartite graphs
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//! - BMF: Boolean matrix factorization
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//! Use [`prelude`] for convenient imports.
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pub mod config;
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pub mod error;

‎src/models/mod.rs‎

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//! Problem model implementations.
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//!
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//! This module contains implementations of various NP-hard problems.
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//!
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//! # Problem Categories
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//!
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//! - **Satisfiability**: SAT, K-SAT, CircuitSAT, Factoring
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//! - **Graph**: MaximumIndependentSet, MaximalIS, MinimumVertexCover, MinimumDominatingSet, KColoring, MaximumMatching, TravelingSalesman
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//! - **Set**: MinimumSetCovering, MaximumSetPacking
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//! - **Optimization**: MaxCut, SpinGlass, QUBO
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//! - **Specialized**: Paintshop, BicliqueCover, BMF
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//! Each sub-module groups related problem types. See individual modules for details.
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pub mod graph;
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pub mod optimization;

‎src/topology/mod.rs‎

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//! Graph topology types.
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//!
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//! This module provides the [`Graph`] trait and various graph implementations:
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//!
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//! - [`SimpleGraph`]: Standard unweighted graph (default for most problems)
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//! - [`UnitDiskGraph`]: Vertices with 2D positions, edges based on distance
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//! - [`HyperGraph`]: Edges can connect any number of vertices
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//!
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//! # Design Philosophy
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//!
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//! Following Julia's Graphs.jl pattern, problems are generic over graph type:
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//!
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//! ```
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//! use problemreductions::topology::{Graph, SimpleGraph, UnitDiskGraph};
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//! use problemreductions::models::graph::MaximumIndependentSet;
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//!
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//! // Problems work with any graph type - SimpleGraph by default
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//! let graph = SimpleGraph::new(3, vec![(0, 1)]);
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//! let simple_graph_problem = MaximumIndependentSet::new(graph, vec![1i32; 3]);
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//! assert_eq!(simple_graph_problem.graph().num_vertices(), 3);
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//!
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//! // Different graph topologies enable different reduction algorithms
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//! // (UnitDiskGraph example would require specific constructors)
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//! ```
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//! - [`PlanarGraph`]: Planar graph
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//! - [`BipartiteGraph`]: Bipartite graph
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//! - [`UnitDiskGraph`]: Vertices with 2D positions, edges based on distance
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//! - [`KingsSubgraph`]: 8-connected grid graph (King's graph)
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//! - [`TriangularSubgraph`]: Triangular lattice subgraph
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mod bipartite_graph;
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mod graph;

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