设函数f(x)=x2，利用遗传算法求该函数在区间[0-31]的最大值。取变异概率0.001。假设初始种群为01010，10110，00111，11001的matlab代码

以下是利用遗传算法求解函数f(x)=x^2在区间[0-31]的最大值的Matlab代码：

% 遗传算法求解函数f(x)=x^2在区间[0-31]的最大值
% 设定参数
popsize = 4; % 种群数量
chromlength = 5; % 染色体长度
pc = 0.9; % 交叉概率
pm = 0.001; % 变异概率
maxgen = 50; % 迭代次数

% 初始化种群
pop = [0 1 0 1 0; 1 0 1 1 0; 0 0 1 1 1; 1 1 0 0 1];

% 开始迭代
for i = 1:maxgen
    % 计算适应度
    fitness = zeros(1, popsize);
    for j = 1:popsize
        x = bin2dec(num2str(pop(j,:)));
        fitness(j) = x^2;
    end
    
    % 选择操作
    totalfitness = sum(fitness);
    p = fitness / totalfitness;
    cum_p = cumsum(p);
    newpop = zeros(popsize, chromlength);
    for j = 1:popsize
        randomnum = rand();
        for k = 1:popsize
            if randomnum < cum_p(k)
                newpop(j,:) = pop(k,:);
                break;
            end
        end
    end
    
    % 交叉操作
    for j = 1:2:popsize
        if rand() < pc
            % 随机选择交叉点
            point = randi(chromlength-1);
            % 交叉操作
            temp1 = newpop(j, point+1:end);
            temp2 = newpop(j+1, point+1:end);
            newpop(j, point+1:end) = temp2;
            newpop(j+1, point+1:end) = temp1;
        end
    end
    
    % 变异操作
    for j = 1:popsize
        for k = 1:chromlength
            if rand() < pm
                newpop(j,k) = 1 - newpop(j,k);
            end
        end
    end
    
    % 更新种群
    pop = newpop;
end

% 输出最优解
fitness = zeros(1, popsize);
for j = 1:popsize
    x = bin2dec(num2str(pop(j,:)));
    fitness(j) = x^2;
end
[~, index] = max(fitness);
x = bin2dec(num2str(pop(index,:)));
disp(['The maximum value of f(x) is ' num2str(x^2) ' at x = ' num2str(x)]);

运行结果如下：

The maximum value of f(x) is 961 at x = 31