基于遗传算法路径规划的MATLAB代码

以下是一个基于遗传算法的路径规划的MATLAB代码示例：

clc;
clear;
close all;

% 地图大小
map_size = [20, 20];

% 障碍物位置
obstacle = [3,3;4,3;5,3;6,3;7,3;7,4;7,5;7,6;7,7;6,7;5,7;4,7;3,7;3,6;3,5;3,4];
obstacle_num = size(obstacle, 1);

% 起点和终点
start_point = [1,1];
end_point = [20,20];

% 遗传算法参数
population_size = 100;
gene_length = 100;
generation = 100;
cross_rate = 0.8;
mutation_rate = 0.01;

% 初始化种群
population = randi([0, 1], population_size, gene_length);

% 开始遗传算法
for i = 1:generation
    % 计算适应度
    fitness = zeros(population_size, 1);
    for j = 1:population_size
        path = decode(population(j, :), map_size);
        fitness(j) = evaluate(path, obstacle, start_point, end_point);
    end
    
    % 选择
    selected_population = selection(population, fitness);
    
    % 交叉
    crossed_population = crossover(selected_population, cross_rate);
    
    % 变异
    mutated_population = mutation(crossed_population, mutation_rate);
    
    % 合并新一代种群
    population = [selected_population; crossed_population; mutated_population];
end

% 找到最优路径
best_fitness = 0;
best_path = [];
for i = 1:population_size
    path = decode(population(i, :), map_size);
    fitness = evaluate(path, obstacle, start_point, end_point);
    if fitness > best_fitness
        best_fitness = fitness;
        best_path = path;
    end
end

% 绘制地图
figure;
hold on;
axis([0, map_size(1), 0, map_size(2)]);
for i = 1:obstacle_num
    rectangle('Position',[obstacle(i, 1)-0.5,obstacle(i, 2)-0.5,1,1],'FaceColor',[0.5 0.5 0.5],'EdgeColor','none');
end
plot(start_point(1), start_point(2), 'ro', 'MarkerSize', 10);
plot(end_point(1), end_point(2), 'r*', 'MarkerSize', 10);

% 绘制路径
for i = 1:length(best_path)-1
    x = [best_path(i, 1), best_path(i+1, 1)];
    y = [best_path(i, 2), best_path(i+1, 2)];
    line(x, y, 'Color', 'r', 'LineWidth', 2);
end

其中，`decode` 函数将一个二进制编码的个体解码为一个路径，`evaluate` 函数计算该路径的适应度，`selection` 函数对种群进行选择，`crossover` 函数进行交叉，`mutation` 函数进行变异。在代码中，路径的表示方式采用了一个二维坐标数组，例如 `[1, 1; 1, 2; 2, 2; 3, 2; ...]` 表示从起点开始，依次经过了 $(1,1)$、$(1,2)$、$(2,2)$、$(3,2)$ 等点，并最终到达终点。