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.

Hint:

  1. Try to solve it in one dimension first. How can this solution apply to the two dimension case?

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,题目中给了提示,让从一维的情况来分析,先看一维时有两个点A和B的情况,

______A_____P_______B_______

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,现在再加两个点C和D:

______C_____A_____P_______B______D______

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,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,参见代码如下:

解法一:

class Solution {
public:
int minTotalDistance(vector<vector<int>>& grid) {
vector<int> rows, cols;
for (int i = ; i < grid.size(); ++i) {
for (int j = ; j < grid[i].size(); ++j) {
if (grid[i][j] == ) {
rows.push_back(i);
cols.push_back(j);
}
}
}
return minTotalDistance(rows) + minTotalDistance(cols);
}
int minTotalDistance(vector<int> v) {
int res = ;
sort(v.begin(), v.end());
int i = , j = v.size() - ;
while (i < j) res += v[j--] - v[i++];
return res;
}
};

我们也可以不用多写一个函数,直接对 rows 和 cols 同时处理,稍稍能简化些代码:

解法二:

class Solution {
public:
int minTotalDistance(vector<vector<int>>& grid) {
vector<int> rows, cols;
for (int i = ; i < grid.size(); ++i) {
for (int j = ; j < grid[i].size(); ++j) {
if (grid[i][j] == ) {
rows.push_back(i);
cols.push_back(j);
}
}
}
sort(cols.begin(), cols.end());
int res = , i = , j = rows.size() - ;
while (i < j) res += rows[j] - rows[i] + cols[j--] - cols[i++];
return res;
}
};

Github 同步地址:

https://github.com/grandyang/leetcode/issues/296

类似题目:

Minimum Moves to Equal Array Elements II

Shortest Distance from All Buildings

参考资料:

https://leetcode.com/problems/best-meeting-point/

https://leetcode.com/problems/best-meeting-point/discuss/74186/14ms-java-solution

https://leetcode.com/problems/best-meeting-point/discuss/74244/Simple-Java-code-without-sorting.

https://leetcode.com/problems/best-meeting-point/discuss/74193/Java-2msPython-40ms-two-pointers-solution-no-median-no-sort-with-explanation

LeetCode All in One 题目讲解汇总(持续更新中...)

[LeetCode] Best Meeting Point 最佳开会地点的更多相关文章

  1. [LeetCode] 296. Best Meeting Point 最佳开会地点

    A group of two or more people wants to meet and minimize the total travel distance. You are given a ...

  2. [Swift]LeetCode296. 最佳开会地点 $ Best Meeting Point

    A group of two or more people wants to meet and minimize the total travel distance. You are given a ...

  3. [LeetCode] 253. Meeting Rooms II 会议室 II

    Given an array of meeting time intervals consisting of start and end times [[s1,e1],[s2,e2],...] (si ...

  4. LeetCode 252. Meeting Rooms (会议室)$

    Given an array of meeting time intervals consisting of start and end times [[s1,e1],[s2,e2],...] (si ...

  5. [LeetCode] 253. Meeting Rooms II 会议室之二

    Given an array of meeting time intervals consisting of start and end times [[s1,e1],[s2,e2],...] (si ...

  6. [LeetCode] 252. Meeting Rooms 会议室

    Given an array of meeting time intervals consisting of start and end times [[s1,e1],[s2,e2],...] (si ...

  7. [LeetCode] Best Meeting Point

    Problem Description: A group of two or more people wants to meet and minimize the total travel dista ...

  8. [LeetCode#253] Meeting Rooms II

    Problem: Given an array of meeting time intervals consisting of start and end times [[s1,e1],[s2,e2] ...

  9. [LeetCode#252] Meeting Rooms

    Problem: Given an array of meeting time intervals consisting of start and end times [[s1,e1],[s2,e2] ...

随机推荐

  1. 6.C#WinForm基础城市选择器

    源码如下: using System; using System.Collections.Generic; using System.ComponentModel; using System.Data ...

  2. Android指纹识别深入浅出分析到实战(6.0以下系统适配方案)

    指纹识别这个名词听起来并不陌生,但是实际开发过程中用得并不多.Google从Android6.0(api23)开始才提供标准指纹识别支持,并对外提供指纹识别相关的接口.本文除了能适配6.0及以上系统, ...

  3. 基础总结之Activity

    一.万事开头的序 网上看见大牛们的博客写的那样精彩,各种羡慕之情溢于言表.几次冲动均想效仿牛人写些博客来记录下自己的心得体会,但均无感亦或是感觉容易被喷,相信很多菜鸟和我一样都有过这样的担忧.万事开头 ...

  4. 在MongoDB的MapReduce上踩过的坑

    太久没动这里,目前人生处于一个新的开始.这次博客的内容很久前就想更新上来,但是一直没找到合适的时间点(哈哈,其实就是懒),主要内容集中在使用Mongodb时的一些隐蔽的MapReduce问题: 1.R ...

  5. 多线程中的volatile和伪共享

      伪共享 false sharing,顾名思义,“伪共享”就是“其实不是共享”.那什么是“共享”?多CPU同时访问同一块内存区域就是“共享”,就会产生冲突,需要控制协议来协调访问.会引起“共享”的最 ...

  6. 四种解析和创建方式(DOM,SAX,DOM4J,JDOM)

    一.先导入jar包 DOM基于树形,SAX基于事件,DOM4J和JDOM基于底层API 二.代码如下 1 package com.sxt.test; import java.io.File; impo ...

  7. 关于Three.js基本几何形状之SphereGeometry球体学习

    一.有关球体SphereGeometry构造函数参数说明 <1>.SphereGeometry(radius, widthSegments, heightSegments, phiStar ...

  8. Linux2.6内核进程调度系列--scheduler_tick()函数3.更新普通进程的时间片

    RT /** * 运行到此,说明进程是普通进程.现在开始更新普通进程的时间片. */ /* 首先递减普通进程的时间片计数器.如果用完,继续执行以下操作 */ if (!--p->time_sli ...

  9. Appfuse:记录操作日志

    appfuse的数据维护操作都发生在***form页面,与之对应的是***FormController,在Controller中处理数据的操作是onSubmit方法,既然所有的操作都通过onSubmi ...

  10. response和request的区别以及常见问题解决

    request是请求,即客服端发来的请求 response是响应,是服务器做出的响应 --------------------------------------------------------- ...