#pragma once
/*
* Copyright (C) 2024 Brett Terpstra
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see .
*/
#ifndef GENETIC_ALGORITHM_H
#define GENETIC_ALGORITHM_H
#include
#include
#include
#include
namespace sky
{
struct individual_t
{
solution_t solution;
blt::i32 fitness = std::numeric_limits::max();
individual_t(solution_t solution, const blt::i32 fitness): solution(std::move(solution)), fitness(fitness)
{
}
void replace(const problem_t& problem, const solution_t& new_solution)
{
solution = new_solution;
fitness = solution.fitness(problem);
}
};
class genetic_algorithm
{
public:
genetic_algorithm(problem_t problem, const blt::i32 individual_count, const double crossover_rate = 0.8, const double mutation_rate = 0.1):
crossover_rate(crossover_rate), mutation_rate(mutation_rate), m_problem(std::move(problem))
{
for (blt::i32 i = 0; i < individual_count; i++)
{
solution_t solution{problem.board_size};
solution.init(problem);
individuals.emplace_back(solution, solution.fitness(m_problem));
}
}
void run_step(blt::i32 elites = 2, blt::i32 k = 5);
[[nodiscard]] double average_fitness() const;
[[nodiscard]] std::vector get_best(blt::i32 amount);
[[nodiscard]] blt::random::random_t& get_random() const;
[[nodiscard]] const solution_t& select(blt::i32 k = 5) const;
[[nodiscard]] std::pair crossover(solution_t first, solution_t second) const;
[[nodiscard]] solution_t mutate(solution_t individual) const;
private:
double crossover_rate, mutation_rate;
problem_t m_problem;
std::vector individuals;
};
}
#endif //GENETIC_ALGORITHM_H