genetic_algorithm.h

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// SPDX-License-Identifier: AGPL-3.0-only
// Copyright (C) 2026 Artificial Intelligence Techniques, S.L. and Roberto López González
 
#pragma once
 
#include "opennn/model_selection/input_selection.h"
 
namespace opennn
{
 
class GeneticAlgorithm final : public InputSelection
{
 
public:
 
    explicit GeneticAlgorithm(Training* = nullptr);
    Index get_individuals_number() const { return population.rows(); }
 
    Index get_genes_number() const { return original_input_indices.size(); }
 
    void set_default();
    const string& get_initialization_method() const noexcept { return initialization_method; }
    void set_initialization_method(const string&);
 
    Index get_minimum_inputs_number() const override { return minimum_inputs_number; }
    Index get_maximum_inputs_number() const override { return maximum_inputs_number; }
 
    void set_minimum_inputs_number(const Index new_minimum) { minimum_inputs_number = new_minimum; }
    void set_maximum_inputs_number(const Index);
 
    void set_individuals_number(const Index new_individuals_number = 4);
 
    void set_mutation_rate(const float rate) { mutation_rate = clamp(rate, 0.0f, 1.0f); }
 
    void set_elitism_size(const Index size) { elitism_size = clamp<Index>(size, 0, get_individuals_number()); }
 
    InputSelectionResult perform_input_selection() override;
 
    void from_JSON(const JsonDocument&) override;
 
    void to_JSON(JsonWriter&) const override;
 
private:
 
    void initialize_population();
    void initialize_population_random();
    void initialize_population_correlations();
    void evaluate_population();
    void assign_fitness();
    void perform_selection();
    VectorB crossover(const VectorB&, const VectorB&) const;
    void perform_crossover();
    void perform_mutation();
    vector<Index> get_selected_indices() const;
 
    vector<Index> genes_to_variable_indices(const VectorB&) const;
 
    Tensor<VectorR, 1> individual_parameters;
 
    vector<Index> original_input_indices;
    vector<Index> original_target_indices;
 
    MatrixB population;
 
    VectorR training_errors;
 
    VectorR validation_errors;
 
    VectorR fitness;
 
    VectorB selected;
 
    Index minimum_inputs_number = 1;
    Index maximum_inputs_number = 0;
 
    float mutation_rate = 0.05f;
 
    Index elitism_size = 10;
 
    string initialization_method = "Random";
};
 
}