区间图上可带负权的2-中位选址问题

本文研究了区间图上可带负权的2-中位选址问题.根据目标函数的不同,可带负权的$p-$中位选址问题($p\geq 2$)可分为两类：即 MWD 和 WMD 模型;前者是所有顶点与服务该顶点的设施之间的最小权重距离之和,后者是所有顶点与相应设施之间的权重最小距离之和.在本篇论文中,我们讨论了区间图上可带负权2-中位选址问题的两类模型,并分别设计时间复杂度为$O(n^2)$的多项式时间算法.     

区间图上可带负权的2-中位选址问题（英文）

Abstract本文研究了区间图上可带负权的2-中位选址问题.根据目标函数的不同,可带负权的p-中位选址问题（p≥2）可分为两类：即MWD和WMD模型;前者是所有顶点与服务该顶点的设施之间的最小权重距离之和,后者是所有顶点与相应设施之间的权重最小距离之和.在本篇论文中,我们讨论了区间图上可带负权2-中位选址问题的两类模型,并分别设计时间复杂度为O（n~2）的多项式时间算法.     

正棱柱、锥、台及正多面体上的最大点

我们知道,正多边形的最大点(到各顶点距离之和最大的点)在顶点;正多面体的最小点(到各顶点距离之和最小的点)在它的中心.基于同正多边形的类比和"最大点应离最小点尽可能远"这样的认识,我们可做出     

一类网络上的干线选址

考虑一类在网络上点到路的距离意义下的最优干线选址问题,这是一类新型的选址问题.首先证明所讨论的两个问题是NP-hard,然后讨论树的情况,给出了当G是树时求解问题的算法,该算法的复杂性是O(n2).并对一些特殊网络的情况进行了讨论.     

点面距离，一招三式

求点到平面的距离是立体几何的重要内容 ,在高考中也经常出现 ,并且直线到平面的距离 ,两个平面间的距离也可以转化成点到平面的距离去求解 .因此 ,点面距离就成了这一类距离问题的交汇点 .直接作出点面距离而得解的例题不多 ,很多情况下都必须把点面距离通过转化变换成较为熟悉简单的模型求解 .本文给出求解点面距离的一招三式———一招 :转化思想 ;三式 :等积转化 ,平行转化 ,比例转化 .下面通过几个具体例子一起来探索题型规律 ,掌握相应的解题方法 .1　等积转化———构造三棱锥模型通过三棱锥模型 ,把点面距离看成棱锥的顶点到对面三…     

棱锥外接球问题突破策略

<正>几何体外接球球心的本质特征是到几何体各顶点距离相等的点.平面中,到线段两端点距离相等的点在它的中垂线上;到多边形各顶点距离相等的点为该多边形的外心.类比到空间,可得:外接球球心在几何体任意一条棱的中垂面上;外接球的球心在经过几何体任意一个面的外心且与此平面垂直的直线上.所以如何交出球心是关键,一般是先找出几何体某一     

顾客为子树结构的树上反中心选址问题

顾客为子树结构的树上反中心选址问题是在树T上寻找一点(位于顶点处或在边的内部),使得该点与子树结构的顾客之间的最小赋权带加数距离尽可能地大.给出了该问题的一个有效算法,其时间复杂度为O(cn+sum from j=1 to m n_j),其中n_j为各子树T_j的顶点个数,c为不同的子树权重个数,n为树的顶点数.     

例谈直线上最短距离的求解方法

<正>1.由特殊到一般,理解数轴上两点之间的距离我们知道,|a|表示数a到原点的距离,这是绝对值的几何意义.进一步地,数轴上两个点A、B分别用a、b表示,那么A、B两点之间的距离为AB=|a-b|.(思考下,为什么?)利用此结论,回答以下问题:(1)数轴上表示2和5的两点之问的距离     

哈明距离下圈图上1-重心问题的反问题

主要讨论哈明距离下圈图上1-重心问题的反问题.1-重心问题的反问题主要研究如何尽可能少地改变网络中的参数值,使得给定的顶点到其它顶点的加权距离之和不超过一个给定的上界.通过将该问题转化为0-1背包问题,证明了在哈明距离下该问题是NP困难的,并运用动态规划的思想,在考虑改变边的长度的情况下,对圈图进行了求解.     

网络选址中对中心点和中位点问题的综合考虑

针对目前网络选址研究中大多分别研究中心点和中位点的片面性,分析综合考虑中心点和中位点的网络选址问题.首先提出对中心点和中位点进行综合考虑的问题,然后通过两个具体的实例,分别建立了综合考虑网络选址的中心点和中位点、绝对中心点和绝对中位点的两个模型,并给出了相应的求解方法、步骤和结果.     

Bounds on Special Subsets in Graphs, Eigenvalues and Association Schemes

We give a bound on the sizes of two sets of vertices at a given minimum distance in a graph in terms of polynomials and the Laplace spectrum of the graph. We obtain explicit bounds on the number of vertices at maximal distance and distance two from a given vertex, and on the size of two equally large sets at maximal distance. For graphs with four eigenvalues we find bounds on the number of vertices that are not adjacent to a given vertex and that have µ common neighbours with that vertex. Furthermore we find that the regular graphs for which the bounds are tight come from association schemes.     

Allocating Vertex π-Guards in Simple Polygons via Pseudo-Triangulations

We use the concept of pointed pseudo-triangulations to establish new upper and lower bounds on a well known problem from the area of art galleries: What is the worst case optimal number of vertex π-guards that collectively monitor a simple polygon with n vertices? Our results are as follows: (1) Any simple polygon with n vertices can be monitored by at most \lfloor n/2 \rfloor general vertex π-guards. This bound is tight up to an additive constant of 1. (2) Any simple polygon with n vertices, k of which are convex, can be monitored by at most \lfloor (2n – k)/3 \rfloor edge-aligned vertexπ-guards. This is the first non-trivial upper bound for this problem and it is tight for the worst case families of polygons known so far.     

Vertex-Colored Encompassing Graphs

It is shown that every disconnected vertex-colored plane straight line graph with no isolated vertices can be augmented (by adding edges) into a connected plane straight line graph such that the new edges respect the coloring and the degree of every vertex increases by at most two. The upper bound for the increase of vertex degrees is best possible: there are input graphs that require the addition of two new edges incident to a vertex. The exclusion of isolated vertices is necessary: there are input graphs with isolated vertices that cannot be augmented to a connected vertex-colored plane straight line graph.     

A Network Improvement Problem Under Different Norms

In this paper, we first consider a network improvement problem, called vertex-to-vertices distance reduction problem. The problem is how to use a minimum cost to reduce lengths of the edges in a network so that the distances from a given vertex to all other vertices are within a given upper bound. We use l , l ₁ and l ₂ norms to measure the total modification cost respectively. Under l norm, we present a strongly polynomial algorithm to solve the problem, and under l ₁ or weighted l ₂ norm, we show that achieving an approximation ratio O(log(|V|)) is NP-hard. We also extend the results to the vertex-to-points distance reduction problem, which is to reduce the lengths of edges most economically so that the distances from a given vertex to all points on the edges of the network are within a given upper bound.     

Generalized steiner problem in series-parallel networks

The generalized Steiner problem (GSP) is concerned with the determination of a minimum cost subnetwork of a given network where some (not necessarily all) vertices satisfy certain pairwise (vertex or edge) connectivity requirements. The GSP has applications to the design of water and electricity supply networks, communication networks and other large-scale systems where connectivity requirements ensure the communication between the selected vertices when some vertices and/or edges can become inoperational due to scheduled maintenance, error, or overload. The GSP is known to be NP-complete. In this paper we show that if the subnetwork is required to be respectively biconnected and edge-biconnected, and the underlying network is series-parallel, both problems can be solved in linear time.     

A stabilized column generation scheme for the traveling salesman subtour problem

Given an undirected graph with edge costs and both revenues and weights on the vertices, the traveling salesman subtour problem is to find a subtour that includes a depot vertex, satisfies a knapsack constraint on the vertex weights, and that minimizes edge costs minus vertex revenues along the subtour.We propose a decomposition scheme for this problem. It is inspired by the classic side-constrained 1-tree formulation of the traveling salesman problem, and uses stabilized column generation for the solution of the linear programming relaxation. Further, this decomposition procedure is combined with the addition of variable upper bound (VUB) constraints, which improves the linear programming bound. Furthermore, we present a heuristic procedure for finding feasible subtours from solutions to the column generation problems. An extensive experimental analysis of the behavior of the computational scheme is presented.     

Bounds on cost effective domination numbers

A vertex υ in a set S is said to be cost effective if it is adjacent to at least as many vertices in V\S as it is in S and is very cost effective if it is adjacent to more vertices in V\S than to vertices in S. A dominating set S is (very) cost effective if every vertex in S is (very) cost effective. The minimum cardinality of a (very) cost effective dominating set of G is the (very) cost effective domination number of G. Our main results include a quadratic upper bound on the very cost effective domination number of a graph in terms of its domination number. The proof of this result gives a linear upper bound for hereditarily sparse graphs which include trees. We show that no such linear bound exists for graphs in general, even when restricted to bipartite graphs. Further, we characterize the extremal trees attaining the bound. Noting that the very cost effective domination number is bounded below by the domination number, we show that every value of the very cost effective domination number between these lower and upper bounds for trees is realizable. Similar results are given for the cost effective domination number.     

一类直径为2的极大平面图的Mostar指数

图G的Mostar指数定义为Mo(G)=∑uv∈Ε(G)|nu-nv|,其中nu表示在G中到顶点u的距离比到顶点v的距离近的顶点个数,nv表示到顶点v的距离比到顶点u的距离近的顶点个数.若一个图G的任两点之间的距离至多为2,且不是完全图,则称G是一个直径为2的图.已知直径为2点数至少为4的极大平面图的最小度为3或4.本文研究了直径为2且最小度为4的极大平面图的Mostar指数.具体说,若G是一个点数为n,直径为2,最小度为4的极大平面图,则(1)当n≤12时,Mostar指数被完全确定;(2)当n≥13时,4/3n2-44/3n+94/3≤Mo(G)≤2n2-16n+24,且达到上,下界的极图同时被找到.     

笛卡尔乘积图里的最小k-路点覆盖

对于子集$S\subseteq V(G)$,如果图$G$里的每一条$k$路都至少包含$S$中的一个点,那么我们称集合$S$是图$G$的一个$k$-路点覆盖.很明显,这个子集并不唯一.我们称最小的$k$-路点覆盖的基数为$k$-路点覆盖数, 记作$\psi_k(G)$.本文给出了一些笛卡尔乘积图上$\psi_k(G)$值的上界或下界.