如果给出了矩阵链,则我们必须找到要相乘的最小正确矩阵序列数。
我们知道矩阵乘法是关联的,因此四个矩阵ABCD可以在这些序列中乘以A(BCD),(AB)(CD),(ABC)D,A(BC)D。像这些序列一样,我们的任务是找到可以有效相乘的顺序。
在给定的输入中,有一个数组说arr,其中包含arr [] = {1,2,3,4}。这意味着矩阵的数量级为(1 x 2),(2 x 3),(3 x 4)。
输入-输入矩阵的阶数。{1,2,3,4}。这意味着矩阵是
{(1 x 2), (2 x 3), (3 x 4)}.
输出-最小操作数需要将这三个矩阵相乘。结果是18。
matOrder(array, n) Input: List of matrices, the number of matrices in the list. Output: Minimum number of matrix multiplication. Begin define table minMul of size n x n, initially fill with all 0s for length := 2 to n, do for i:=1 to n-length, do j := i + length – 1 minMul[i, j] := ∞ for k := i to j-1, do q := minMul[i, k] + minMul[k+1, j] + array[i-1]*array[k]*array[j] if q < minMul[i, j], then minMul[i, j] := q done done done return minMul[1, n-1] End
#include<iostream> using namespace std; int matOrder(int array[], int n){ int minMul[n][n]; //holds the number of scalar multiplication needed for (int i=1; i<n; i++) minMul[i][i] = 0; //for multiplication with 1 matrix, cost is 0 for (int length=2; length<n; length++){ //find the chain length starting from 2 for (int i=1; i<n-length+1; i++){ int j = i+length-1; minMul[i][j] = INT_MAX; //set to infinity for (int k=i; k<=j-1; k++){ //每次存储的存储成本 int q = minMul[i][k] + minMul[k+1][j] + array[i-1]*array[k]*array[j]; if (q < minMul[i][j]) minMul[i][j] = q; } } } return minMul[1][n-1]; } int main(){ int arr[] = {1, 2, 3, 4}; int size = 4; cout << "Minimum number of matrix multiplications: "<<matOrder(arr, size); }
输出结果
Minimum number of matrix multiplications: 18