This problem can be solved by computing the maximum flow in the graph(you can use Dinic's algorithm). You should create a graph with n (children) + m (toys) + 2 (source and sink), edges from each child to each toy, which he want to get. The capacity of each edge should be 1. And now you should just find the maximum flow.

If the constraints are small like the matrix is 20 by 20 we can use dp + bit masking. Refer to this problem to gain some idea about dp + bit masking. https://www.spoj.com/problems/ASSIGN/

Here is the code:

int n;
int memo[1<<20][20];
int matrix[20][20];
int dp(int mask, int i)
{
  if(memo[mask][i] != -1)
        return memo[mask][i];

  int ans = 0;
  for(int j = 0; j < n; j++)
    if( !(mask&(1<<j)) )//not set
        ans = max(ans, matrix[i][j] + dp(mask|(1<<j), i+1));
  return memo[mask][i] = ans;
}
int main()
{
    cin >> n;
    for(int i = 0; i < n; i++)
        for(int j = 0; j < n; j++)
            cin >> matrix[i][j];
    for(int i = 0; i < (1<<n); i++)
        for(int j = 0; j < n; j++)
            memo[i][j] = -1;
    cout << dp(0, 0);
}

This is known as maximum matching in a bipartite graph and can be solved using Hopcroft Karp