三.蝠鲼觅食优化算法MRFO伪代码

以下是蝠鲼觅食优化算法MRFO的伪代码：

Initialize the population of bats
While stopping criterion is not met:
    For each bat i in the population:
        Generate a new solution x_i by updating the bat's position:
            x_i = x_i + A*sin(2*pi*f)*|r_i,j - x_j|
            where A is the loudness of the bat, f is the frequency, r_i,j is the position of a randomly selected bat, and x_j is the position of the best bat in the population
        If the new solution x_i is better than the current solution x_i, replace x_i with the new solution
        With probability r_i, generate a new solution x_i by random walk:
            x_i = x_i + epsilon_i
            where epsilon_i is a vector of random values drawn from a normal distribution
        Update the loudness A and frequency f of the bat:
            A = alpha*A
            f = f_min + (f_max - f_min)*rand()
        If the loudness A is less than a threshold value A_min, reset the bat's position to a new random solution
        If the new solution x_i is better than the best solution in the population, update the best solution
    End for
End while

其中，蝠鲼觅食优化算法通过模拟蝙蝠觅食的行为来进行优化。每个蝙蝠代表一个潜在解，其位置表示解的参数值。蝙蝠根据当前最优解和其他蝙蝠的位置信息来更新自己的位置。此外，每个蝙蝠还具有一个“响度”和“频率”的属性，可以调整其搜索范围和速度。在搜索过程中，每个蝙蝠还有一定概率进行随机游走以增加搜索多样性。最终，算法的输出结果是最优解。