Given a triangle, find the minimum path sum from top to bottom. Each step you may move to adjacent numbers on the row below.
For example, given the following triangle
[
[2],
[3,4],
[6,5,7],
[4,1,8,3]
]
The minimum path sum from top to bottom is 11
(i.e., 2 + 3 + 5 + 1 = 11
).
Note: Bonus point if you are able to do this using only O(n) extra space, where n is the total number of rows in the triangle.
典型DP,显然dp[i][j] = min(dp[i - 1][j], dp[i - 1][j - 1]
, 因此
int minimumTotal(vector<vector<int>> &a) {
int n = a.size();
if (n < 1)
return 0;
vector<vector<int>> dp(n, vector<int>(n, 0));
dp[0][0] = a[0][0];
for (int i = 1; i < n; ++i) {
dp[i][0] = dp[i - 1][0] + a[i][0];
dp[i][i] = dp[i - 1][i - 1] + a[i][i];
for (int j = 1; j < i; ++j) {
dp[i][j] = min(dp[i - 1][j], dp[i - 1][j - 1]) + a[i][j];
}
}
return *min_element(begin(dp[n - 1]), end(dp[n - 1]));
}
最后需要O(n)时间寻找最小值,我们可以从底部推顶部,此时dp[i][j] = min(dp[i + 1][j], dp[i + 1][j + 1]
int minimumTotal(const vector<vector<int>> &a) {
int n = a.size();
if (n < 1)
return 0;
vector<vector<int>> dp(n, vector<int>(n, 0));
for (int i = 0; i < a[n - 1].size(); ++i) {
dp[n - 1][i] = a[n - 1][i];
}
for (int i = n - 2; i >= 0; --i) {
for (int j = 0; j <= i; ++j) {
dp[i][j] = min(dp[i + 1][j], dp[i + 1][j + 1]) + a[i][j];
}
}
return dp[0][0];
}
以上方法都能解决问题,关键是需要O(n2)的空间,题目要求O(n)。
从状态转移方程可以看出,dp[i][j]
只和上一行有关,和其他行无关,我们可以复用这些空间,覆盖原来的值,从而达到压缩空间的效果.
int compress_minimumTotal(const vector<vector<int>> &a) {
int n = a.size();
if (n < 1)
return 0;
vector<int> dp;
for_each(begin(a[n - 1]), end(a[n - 1]), [&dp](int i){dp.push_back(i);});
for (int i = n - 2; i >= 0; --i) {
for (int j = 0; j <= i; ++j) {
dp[j] = min(dp[j], dp[j + 1]) + a[i][j];
}
}
return dp[0];
}