Algorithm to review the problem of stone merging in dynamic programming

The problem of stone merging consists of straight and round shapes:

Straight Type:

The linear lion merge problem has the following recursion:

F[I][J]: The minimum cost of merging from the first heap to the bottom of the J heap

f[i][j]=0; I=j

F[i][j]=min (F[i][k]+f[k+1][j]+sum (i,j)); i<=k<j;

This problem is better understood, according to the recursive, our I to go from high to the end, j to traverse from low to high

The line code is as follows:

#include <iostream> #include <vector>using namespace std;int sum (vector<int> &stone,int l,int R) {        int res=0;        for (int i=l;i<=r;i++) {res+=stone[i]; } return res;        int merge (vector<int> &stone) {int res=0;        int f[100][100]={0};        int len=stone.size ();        for (int i=0;i<len;i++) {f[i][i]=0;                        } for (int i=len-2;i>=0;i--) {for (int j=i+1;j<len;j++) {                        int M=int_max; for (int k=i;k<j;k++) {if (M>f[i][k]+f[k+1][j]+sum (STONE,I,J)                                ) {m=f[i][k]+f[k+1][j]+sum (stone,i,j);                }} f[i][j]=m; }} return f[0][len-1];} int main () {int n=0;       Vector<int> Stone;                while (cin>>n) {stone.clear ();                int a=0;                        for (int i=0;i<n;i++) {cin>>a;                Stone.push_back (a);        } cout<<merge (Stone) <<endl; } return 0;}

Algorithm to review the problem of stone merging in dynamic programming