[LeetCode 296] Best Meeting Poin
A group of two or more people wants to meet and minimize the total travel distance. You are given a 2D grid of values 0 or 1, where each 1 marks the home of someone in the group. The distance is calculated using Manhattan Distance, where distance(p1, p2) = |p2.x - p1.x| + |p2.y - p1.y|
.
Example:
Input:
1 - 0 - 0 - 0 - 1
| | | | |
0 - 0 - 0 - 0 - 0
| | | | |
0 - 0 - 1 - 0 - 0
Output: 6
Explanation:** Given three people living at `(0,0)`, `(0,4)`, and `(2,2)`:
The point `(0,2)` is an ideal meeting point, as the total travel distance
of 2+2+2=6 is minimal. So return 6.
Solution
引用自https://www.cnblogs.com/grandyang/p/5291058.html
这道题让我们求最佳的开会地点,该地点需要到每个为1的点的曼哈顿距离之和最小,题目中给了我们提示,让我们先从一维的情况来分析,那么我们先看一维时有两个点A和B的情况,
______A_____P_______B_______
那么我们可以发现,只要开会为位置P在[A, B]区间内,不管在哪,距离之和都是A和B之间的距离,如果P不在[A, B]之间,那么距离之和就会大于A和B之间的距离,那么我们现在再加两个点C和D:
______C_____A_____P_______B______D______
我们通过分析可以得出,P点的最佳位置就是在[A, B]区间内,这样和四个点的距离之和为AB距离加上CD距离,在其他任意一点的距离都会大于这个距离,那么分析出来了上述规律,这题就变得很容易了,我们只要给位置排好序,然后用最后一个坐标减去第一个坐标,即CD距离,倒数第二个坐标减去第二个坐标,即AB距离,以此类推,直到最中间停止,那么一维的情况分析出来了,二维的情况就是两个一维相加即可
class Solution {
public int minTotalDistance(int[][] grid) {
if (grid == null || grid.length == 0 || grid[0].length == 0) {
return -1;
}
List<Integer> rows = new ArrayList<> ();
List<Integer> cols = new ArrayList<> ();
for (int i = 0; i < grid.length; i++) {
for (int j = 0; j < grid[0].length; j++) {
if (grid[i][j] == 1) {
rows.add (i);
cols.add (j);
}
}
}
return minTotalDistanceHelper (rows) + minTotalDistanceHelper (cols);
}
public int minTotalDistanceHelper (List<Integer> coordinates) {
Collections.sort (coordinates);
int result = 0;
int start = 0;
int end = coordinates.size () - 1;
while (start < end) {
result += coordinates.get (end --) - coordinates.get (start ++);
}
return result;
}
}