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