题意:求最小生成树第K大的边权值 思路: 如果暴力加边再用Kruskal,边太多会超时.这里用一个算法来减少有效边的加入. 边权值为点间曼哈顿距离,那么每个点的有效加边选择应该是和他最近的4个象限方向的点.这里用一个树状数组维护以y-x为索引的y+x的值,然后这个数组所储存的就是一个点的第一象限方向的距离他最近的点.这样我们每次查找只要看(i,N)这个区间是否有一个点的距离比现在的更小(因为以y-x为索引,所以I>i就表示I这个点在i的第一象限方向).最后每个方向的边都加完后,只要用Kruska…

题意:转换一下就是求曼哈顿最小生成树的第n-k条边 参考:莫涛大神的论文<平面点曼哈顿最小生成树> /* Problem: 3241 User: 96655 Memory: 920K Time: 94MS Language: C++ Result: Accepted */ #include<cstdio> #include<cstring> #include<algorithm> #include<iostream> #include<cs…

Position: http://poj.org/problem?id=3241 List Poj3241 Object Clustering List Description Knowledge Solution Notice Code 感谢 Description 大意:求曼哈顿距离最小生成树上第k大(第n-k小)的边. Knowledge 参考曼哈顿距离最小生成树 http://blog.csdn.net/yjpyjp2014/article/details/52180707 Soluti…

Object Clustering   Description We have N (N ≤ 10000) objects, and wish to classify them into several groups by judgement of their resemblance. To simply the model, each object has 2 indexes a and b (a, b ≤ 500). The resemblance of object i and objec…

Object Clustering Time Limit: 2000MS   Memory Limit: 131072K Total Submissions: 2640   Accepted: 806 Description We have N (N ≤ 10000) objects, and wish to classify them into several groups by judgement of their resemblance. To simply the model, each…

http://poj.org/problem?id=3241 (题目链接) MD被坑了,看到博客里面说莫队要写曼哈顿最小生成树,我就写了一个下午..结果根本没什么关系.不过还是把博客写了吧. 转自:http://blog.csdn.net/huzecong/article/details/8576908 题意 求曼哈顿距离最小生成树上第k大(第n-k小)的边 Solution 曼哈顿距离最小生成树问题可以简述如下: 给定二维平面上的${N}$个点,在两点之间连边的代价为其曼哈顿距离,求使所有点连…

http://poj.org/problem?id=3241 曼哈顿距离最小生成树模板题. 核心思想是把坐标系转3次,以及以横坐标为第一关键字,纵坐标为第二关键字排序后,从后往前扫.扫完一个点就把它插到树状数组的y-x位置上,权值为x+y.查询时查询扫过的所有点满足ydone-xdone>=ynow-xnow时,直接是树状数组中的的一个后缀区间,从后往前扫保证了区间内的这些点都在当前点的y轴向右扫45度的范围内.树状数组实现查询x+y的最小值,以及此最小值对应原数组中的位置,方便建图连边. 模板…

先上几个资料: 百度文库有详细的分析和证明 cxlove的博客 TopCoder Algorithm Tutorials #include <cstdio> #include <cstring> #include <algorithm> #include <vector> #include <cmath> using namespace std; + ; const int INF = 0x3f3f3f3f; int n, m, k; struc…

题目链接:http://poj.org/problem?id=3241 Description We have N (N ≤ 10000) objects, and wish to classify them into several groups by judgement of their resemblance. To simply the model, each object has 2 indexes a and b (a, b ≤ 500). The resemblance of ob…

Description We have N (N ≤ 10000) objects, and wish to classify them into several groups by judgement of their resemblance. To simply the model, each object has 2 indexes a and b (a, b ≤ 500). The resemblance of object i and object j is defined by di…