帮我写一个至少二维问题的遗传算法matlab代码

以下是一个使用遗传算法解决二维问题的Matlab代码示例：

% 遗传算法参数设置
populationSize = 50; % 种群大小
numGenerations = 100; % 迭代次数
mutationRate = 0.01; % 变异率

% 问题设置
targetFunction = @(x, y) x^2 + y^2; % 目标函数，这里以二维函数x^2 + y^2为例
variableRange = [-10, 10]; % 变量取值范围

% 初始化种群
population = initializePopulation(populationSize, variableRange);

% 迭代进化
for generation = 1:numGenerations
    % 计算适应度
    fitness = calculateFitness(population, targetFunction);
    
    % 选择
    parents = selection(population, fitness);
    
    % 交叉
    offspring = crossover(parents, populationSize);
    
    % 变异
    mutatedOffspring = mutation(offspring, mutationRate, variableRange);
    
    % 新一代种群
    population = mutatedOffspring;
end

% 最优解
[~, bestIndex] = min(fitness);
bestSolution = population(bestIndex, :);

% 输出最优解
disp(['最优解：x = ', num2str(bestSolution(1)), ', y = ', num2str(bestSolution(2))]);

% 初始化种群函数
function population = initializePopulation(populationSize, variableRange)
    numVariables = length(variableRange);
    population = rand(populationSize, numVariables) .* diff(variableRange) + variableRange(1);
end

% 计算适应度函数
function fitness = calculateFitness(population, targetFunction)
    fitness = targetFunction(population(:, 1), population(:, 2));
end

% 选择函数
function parents = selection(population, fitness)
    [~, sortedIndices] = sort(fitness);
    parents = population(sortedIndices(1:2), :);
end

% 交叉函数
function offspring = crossover(parents, populationSize)
    numVariables = size(parents, 2);
    crossoverPoint = randi(numVariables - 1);
    offspring = zeros(populationSize, numVariables);
    offspring(1:2, :) = parents;
    for i = 3:populationSize
        parentIndex = randi(2);
        parent = parents(parentIndex, :);
        offspring(i, :) = [parent(1:crossoverPoint), parents(3-parentIndex, crossoverPoint+1:end)];
    end
end

% 变异函数
function mutatedOffspring = mutation(offspring, mutationRate, variableRange)
    numVariables = size(offspring, 2);
    mutatedOffspring = offspring;
    for i = 1:size(offspring, 1)
        for j = 1:numVariables
            if rand < mutationRate
                mutatedOffspring(i, j) = rand * diff(variableRange) + variableRange(1);
            end
        end
    end
end

这个代码解决的是一个求解二维函数的最小值问题。你可以根据自己的具体问题进行相应的修改。代码中的初始化种群、计算适应度、选择、交叉和变异等操作都可以根据实际情况进行调整。