38 lines
2.4 KiB
C++
38 lines
2.4 KiB
C++
#ifndef H_differential_evolution
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#define H_differential_evolution
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#include <functional>
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#include <Eigen/Dense>
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namespace differential_evolution {
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/// @brief Result of an optimization algorithm.
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struct OptimizationResult {
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Eigen::VectorXd x; //!< Minimum of the function.
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double fx; //!< Function value at the minimum.
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unsigned int n_iter = 0; //!< Number of iterations.
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bool converged = false; //!< Whether the algorithm converged.
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};
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/// @brief Global minimization of a function using the differential evolution algorithm.
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/// @param f The function to minimize.
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/// @param lb Lower bounds of the parameters.
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/// @param ub Upper bounds of the parameters.
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/// @param tol Tolerance on the standard deviation of the function value among all individuals of the population.
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/// @param n_iter_max Maximum number of iterations.
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/// @param n_individuals Number of individuals in the population. By default, 10 * lb.size(). Must be greater than 4.
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/// @param crossover_proba Crossover probability. Between 0 and 1.
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/// @param differential_weight Differential weight. Between 0 and 2.
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/// @return The result structure containing the minimum of the function and the function value at the solution. If res.converged is false, either the algorithm did not converge, or an error occured at the beginning of the function.
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OptimizationResult differential_evolution_minimize( std::function<double(Eigen::VectorXd const&)> f,
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Eigen::VectorXd const& lb,
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Eigen::VectorXd const& ub,
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double tol = 1e-6,
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unsigned int n_iter_max = 1000,
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unsigned int n_individuals = 0,
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double crossover_proba = 0.9,
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double differential_weight = 0.8);
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}// namespace differential_evolution
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#endif
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