81 lines
3.3 KiB
C
81 lines
3.3 KiB
C
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/**
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* @class HungarianAlgorithmEigen
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*
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* @brief Implements the Hungarian Algorithm using the Eigen library for solving the assignment problem.
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*
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* This class is designed to solve the assignment problem, which is to find the minimum cost way of assigning tasks to agents.
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* It makes use of the Eigen library for matrix operations, providing an efficient implementation suitable for large scale problems.
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*
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* Usage:
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* Eigen::MatrixXd cost_matrix = ...; // Define the cost matrix
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* Eigen::VectorXi assignment;
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* HungarianAlgorithmEigen solver;
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* double cost = solver.SolveAssignmentProblem(cost_matrix, assignment);
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*
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* Note:
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* The algorithm assumes that the input cost matrix contains only non-negative values. It is not thread-safe and is designed for single-threaded environments.
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*/
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#pragma once
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#include <iostream>
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#include <Eigen/Dense>
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#include <cfloat>
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namespace ByteTrackEigen {
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// The HungarianAlgorithmEigen class encapsulates the Hungarian Algorithm
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// for solving the assignment problem, which finds the minimum cost matching
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// between elements of two sets. It uses the Eigen library to handle matrix operations.
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class HungarianAlgorithmEigen
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{
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public:
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// Constructor and destructor
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HungarianAlgorithmEigen();
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~HungarianAlgorithmEigen();
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// Solves the assignment problem given a distance matrix and returns the total cost.
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// The assignment of rows to columns is returned in the 'Assignment' vector.
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double solve_assignment_problem(Eigen::MatrixXd& dist_matrix, Eigen::VectorXi& assignment);
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private:
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// Constants used as special values indicating not found or default assignments.
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const int NOT_FOUND_VALUE = -1;
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const int DEFAULT_ASSIGNMENT_VALUE = -1;
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// The distance matrix representing the cost of assignment between rows and columns.
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Eigen::MatrixXd dist_matrix;
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// Matrices and vectors used in the Hungarian algorithm
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Eigen::Array<bool, Eigen::Dynamic, Eigen::Dynamic> star_matrix, new_star_matrix, prime_matrix;
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Eigen::Array<bool, Eigen::Dynamic, 1> covered_columns, covered_rows;
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// Finds a starred zero in a column, if any.
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Eigen::Index find_star_in_column(int col);
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// Finds a primed zero in a row, if any.
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Eigen::Index find_prime_in_row(int row);
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// Updates the star and prime matrices given a row and column.
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void update_star_and_prime_matrices(int row, int col);
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// Reduces the matrix by subtracting the minimum value from each uncovered row
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// and adding it to each covered column, thus creating at least one new zero.
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void reduce_matrix_by_minimum_value();
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// Covers columns without a starred zero and potentially modifies star/prime matrices.
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void cover_columns_lacking_stars();
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// Executes the steps of the Hungarian algorithm.
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void execute_hungarian_algorithm();
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// Initializes helper arrays used by the algorithm.
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void init_helper_arrays(int num_rows, int num_columns);
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// Constructs the assignment vector from the star matrix.
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void construct_assignment_vector(Eigen::VectorXi& assignment);
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// Calculates the total cost of the assignment.
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double calculate_total_cost(Eigen::VectorXi& assignment);
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};
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}
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