k-center问题-学习
k-center问题:
In graph theory, the metric k-center or metric facility location problem is a combinatorial optimization problem studied in theoretical computer science. Given n cities with specified distances, one wants to build k warehouses in different cities and minimize the maximum distance of a city to a warehouse. In graph theory this means finding a set of k vertices for which the largest distance of any point to its closest vertex in the k-set is minimum. The vertices must be in a metric space, providing a complete graph that satisfies the triangle inequality.

G7, a complete graph with 7 vertices

The k-Center Clustering problem can also be defined on a complete undirected graph G = (V, E) as follows:
Given a complete undirected graph G = (V, E) with distances d(vi, vj) ∈ N satisfying the triangle inequality, find a subset C ⊆ V with |C| = k while minimizing:

In a complete undirected graph G = (V, E), if we sort the edges in nondecreasing order of the distances: d(e1) ≤ d(e2) ≤ … ≤ d(em) and let Gi = (V, Ei), where Ei = {e1, e2, …, ei}. The k-center problem is equivalent to finding the smallest index i such that Gi has a dominating set of size at most k.
Dominating set:
In graph theory, a dominating set for a graph G = (V, E) is a subset D of V such that every vertex not in D is adjacent to at least one member of D. The domination number γ(G) is the number of vertices in a smallest dominating set for G.

Dominating sets (red vertices)
The dominating set problem concerns testing whether γ(G) ≤ K for a given graph G and input K; it is a classical NP-complete decision problem in computational complexity theory.Therefore it is believed that there may be no efficient algorithm that finds a smallest dominating set for all graphs, although there are efficient approximation algorithms, as well as both efficient and exact algorithms for certain graph classes.
Figures (a)–(c) on the right show three examples of dominating sets for a graph. In each example, each white vertex is adjacent to at least one red vertex, and it is said that the white vertex is dominated by the red vertex. The domination number of this graph is 2: the examples (b) and (c) show that there is a dominating set with 2 vertices, and it can be checked that there is no dominating set with only 1 vertex for this graph.
For Dominator in control flow graphs, see Dominator (graph theory).
来源于网络
k-center问题-学习的更多相关文章
- K线图学习
本博文(适合入门的股民朋友)内容来自网络,股市有风险,入市需谨慎 一.起源 K线图(Candlestick Charts)又称蜡烛图.日本线.阴阳线.棒线等,常用说法是“K线”,起源于日本十八世纪德川 ...
- bzoj 1598: [Usaco2008 Mar]牛跑步 [k短路 A*] [学习笔记]
1598: [Usaco2008 Mar]牛跑步 题意:k短路 ~~貌似A*的题目除了x数码就是k短路~~ \[ f(x) = g(x) + h(x) \] \(g(x)\)为到达当前状态实际代价,\ ...
- 机器学习2—K近邻算法学习笔记
Python3.6.3下修改代码中def classify0(inX,dataSet,labels,k)函数的classCount.iteritems()为classCount.items(),另外p ...
- The Preliminary Contest for ICPC Asia Xuzhou 2019 K. Center
这题对于能加入最多边缘点的center点,这个点就是最优的center ,对于center点,总共是n^2的,顶多也就1e6,所以直接双重循环就行了, 然后map<pair,set >映射 ...
- 02-16 k近邻算法
目录 k近邻算法 一.k近邻算法学习目标 二.k近邻算法引入 三.k近邻算法详解 3.1 k近邻算法三要素 3.1.1 k值的选择 3.1.2 最近邻算法 3.1.3 距离度量的方式 3.1.4 分类 ...
- 集成学习之Adaboost算法原理小结
在集成学习原理小结中,我们讲到了集成学习按照个体学习器之间是否存在依赖关系可以分为两类,第一个是个体学习器之间存在强依赖关系,另一类是个体学习器之间不存在强依赖关系.前者的代表算法就是是boostin ...
- 小K的H5之旅-实战篇(一)
一.前言 本K在经过两个星期的html和css学习之后,第一次去尝试完成一个网站主页的制作.在四天之后,本K也终于完成了杰瑞教育主页的html和css部分,至于部分涉及js的部分,因为本K还没有学习过 ...
- 集成学习值Adaboost算法原理和代码小结(转载)
在集成学习原理小结中,我们讲到了集成学习按照个体学习器之间是否存在依赖关系可以分为两类: 第一个是个体学习器之间存在强依赖关系: 另一类是个体学习器之间不存在强依赖关系. 前者的代表算法就是提升(bo ...
- 4. 集成学习(Ensemble Learning)Adaboost
1. 集成学习(Ensemble Learning)原理 2. 集成学习(Ensemble Learning)Bagging 3. 集成学习(Ensemble Learning)随机森林(Random ...
- 何时开始phonics学习及配套阅读训练zz
引子:自从11月份俱乐部第一批孩子开始英文阅读,到现在三.四个月的时间过去了.很多孩子从不知道怎么读绘本甚至排斥英语,到现在能很投入地看原版书, 有些甚至主动地去寻找拼读规律.我家小宝目前也从前期的阅 ...
随机推荐
- Software-Defined Networking A Comprehensive Survey --阅读_day1
The Internet has led to the creation of a digital society, where (almost) everything is connected an ...
- 【代码笔记】iOS-计算时间差
一,代码. - (void)viewDidLoad { [super viewDidLoad]; // Do any additional setup after loading the view, ...
- 【读书笔记】iOS-网络-同步请求,队列式异步请求,异步请求的区别
一,同步请求的最佳实践. 1,只在后台过程中使用同步请求,除非确定访问的是本地文件资源,否则请不要在主线程上使用. 2,只有在知道返回的数据不会超出应用的内存时才使用同步请求.记住,整个响应体都会位于 ...
- spring 3.2.2后springjdbc中不用queryforInt了
今天才发现,原来spring 3.2.2之后,jdbctemplate中的queryForInt已经被取消了! 参考博客:http://jackyrong.iteye.com/blog/2086255
- 正则匹配身份证有bug你知道么?
在开发中,我们需要验证用户的输入信息,多半采用正则验证,下面就是身份证证号的几种常用的正则表达式: var reg = /(^\d{15}$)|(^\d{18}$)|(^\d{17}(\d|X|x) ...
- C#与java中的AES加解密互解算法
一.C#版AES加解密算法 public class AESCode { public string Key { get; set; } public string Encrypt(string va ...
- Python 列表(List)操作方法详解
Python 列表(List)操作方法详解 这篇文章主要介绍了Python中列表(List)的详解操作方法,包含创建.访问.更新.删除.其它操作等,需要的朋友可以参考下 列表是Python中最基本 ...
- (转)在.net中检索HTTP请求
原文转载:https://www.west-wind.com/presentations/dotnetWebRequest/dotnetWebRequest.htm HTTP内容检索是应用程序的重要组 ...
- Mac逆向--思维导图
- mysql index hint 在index不存在时的处理
关于index_hint 在mysql查询语句中可以通过指定index_hint来告诉优化器如何使用索引,详细可以参考这里 index_hint: USE {INDEX|KEY} [FOR {JOIN ...