图的区间边着色的收缩图方法

图G的一个用了颜色1,2,…,t的边着色称为区间t-着色,如果所有t种颜色都被用到,并且关联于G的同一个顶点的边上的颜色是各不相同的,且这些颜色构成了一个连续的整数区间.G称作是可区间着色的,如果对某个正整数t,G有一个区间t-着色.所有可区间着色的图构成的集合记作■.对图G∈■,使得G有一个区间t-着色的t的最小值和最大值分别记作ω(G)和W(G).现给出了图的区间着色的收缩图方法.利用此方法,我们对双圈图G∈■,证明了ω(G)=△(G)或△(G)+1,并且完全确定了ω(G)=△(G)及ω(G)=△(G)+1的双圈图类.     

关于区间图的一些有效并行算法

本文基于SIMD-CREW-PRAM一种可同时读但不可同时写的共享计算模型,给出了有关区间图的一些有效的并行算法。如找最大加权集团,最小集团覆盖,等权区间图的最大独立集及最小支配集,真区间图的哈密顿回路及最小带宽。所有这些算法都是最优的,其时间复杂性为O(logn)和处理器数为O(n)。     

区间支付图对策上的平均树解

结合图对策和具有区间支付的模糊合作对策理论,引入区间支付图对策,提出区间平均树解,此解可以看做是经典图对策中平均树解的推广,并通过算例说明区间平均树解的应用性.分析了区间平均树解的相对分支有效性.当区间支付图对策满足严格超可加性时,每个局中人参加联盟得到的收益不小于其单干所得支付.最后,讨论了经典平均树解与区间平均树解之间的关系.     

树的补图的区间图完全化问题

一个图G的区间图完全化问题包含两类子问题:侧廓问题和路宽问题,分别表示为P(G)和PW(G),其中侧廓问题是寻求G的一个边数最小的区间超图;路宽问题是寻求G的一个团数最小的区间超图.这两类子问题分别在数值代数、VLSI-设计和算法图论等学科领域中有重要的应用.对一般图来说,两类子问题都是NP-完全问题;但是对一些特殊图类来说,它们在多项式时间内可解.本文给出了树T的补图的具体侧廓和路宽值.     

具有可变抽样区间的EWMA标准差控制图

对指数加权滑动平均即EWM A标准差控制图进行了可变抽样区间设计,用M arkov-cha in方法给出了该控制图的平均报警时间的计算公式,并同固定抽样区间的常规EWM A标准差控制图进行比较,数据显示,所设计的控制图能较快的发现过程变化从而减少产品的不合格率.     

区间值模糊图的运算性质

证明了区间值强模糊图类对笛卡尔积和合成运算封闭但对并运算和联运算不封闭,给出了它们对并运算和联运算封闭的条件,研究了合成、并、联运算和补运算之间的关系.     

可变抽样区间图经济设计分析

传统控制图是静态的,其抽样区间为固定常数,往往不能及时发现生产过程异常。针对这种情况,本文在综合抽样成本、生产次品损失、误报警和漏报警损失、发现并纠正过程异常成本等基础上,提出可变抽样区间X图的经济设计方法。根据过程实际状态和由抽样结果采取的决策构建了一个二维时间离散的马尔可夫链,提出优化模型,并利用遗传算法寻找控制图参数的最优解。数值计算给出本文模型的具体求解过程。灵敏度分析研究了各参数对最优样本容量、控制限、警戒限、抽样区间及单位时间平均成本的影响。     

赋权图的圆染色与区间染色

赋权图的区间染色的定义与赋权图的圆染色的定义非常类型,唯一的区别就是将Ｇ的顶点对应圆周上的孤换为Ｇ的顶点对应区间上的子区间,讨论了赋权的圆染色与区染色的关系。     

可变抽样区间的二项EWMA控制图

在制造过程中,对产品的不合格品数进行监控时,通常选用计数性控制图-np图,它是基于过程服从二项分布建立的,一般对于过程中出现的较大波动效果明显。为了提高控制图对不合格品数较小波动的监控效果,本文设计了产品不合格品数服从二项分布的EWMA控制图。提出可变抽样区间的二项EWMA控制图,并采用马可夫链法计算其平均报警时间。对固定抽样区间以及可变抽样区间二项EWMA控制图对比研究,表明当过程失控时,可变抽样区间二项EWMA控制图具有较小的失控平均报警时间,能够迅速监测出过程中的异常波动,明显优于固定抽样区间的二项EWMA控制图。     

奇图的匹配可扩性

设G是一个图,n,k和d是三个非负整数,满足n+2k+d≤|V(G)|-2,|V(G)|和n+d有相同的奇偶性.如果删去G中任意n个点后所得的图有k-匹配,并且任一k-匹配都可以扩充为一个亏d-匹配,那么称G是一个(n,k,d)-图.Liu和Yu[1]首先引入了(n,k,d)-图的概念,并且给出了(n,k,d)-图的一个刻划和若干性质. (0,k,1)-图也称为几乎k-可扩图.在本文中,作者改进了(n,k,d)-图的刻划,并给出了几乎k-可扩图和几乎k-可扩二部图的刻划,进而研究了几乎k-可扩图与n-因子临界图之间的关系.     

Completion of the mixed unit interval graphs hierarchy

We describe the missing class of the hierarchy of mixed unit interval graphs. This class is generated by the intersection graphs of families of unit intervals that are allowed to be closed, open, and left‐closed‐right‐open. (By symmetry, considering closed, open, and right‐closed‐left‐open unit intervals generates the same class.) We show that this class lies strictly between unit interval graphs and mixed unit interval graphs. We give a complete characterization of this new class, as well as quadratic‐time algorithms that recognize graphs from this class and produce a corresponding interval representation if one exists. We also show that the algorithm from Shuchat et al. [8] directly extends to provide a quadratic‐time algorithm to recognize the class of mixed unit interval graphs.     

Chordal graphs,interval graphs,and wqo

Let precedes, equal to be the induced-minor relation. It is shown that, for every t, all chordal graphs of clique number at most t are well-quasi-ordered by precedes, equal to. On the other hand, if the bound on clique number is dropped, even the class of interval graphs is not well-quasi-ordered by precedes, equal to. © 1998 John Wiley & Sons, Inc. J Graph Theory 28: 105–114, 1998     

OPTIMAL LABELLING OF UNIT INTERVAL GRAPHS

This paper shows that, for every unit interval graph, there is a labelling which is simultaneously optimal for the following seven graph labelling problems: bandwidth, cyclic bandwidth, profile, fill-in, cutwidth, modified cutwidth, and bandwidth sum(linear arrangement).     

Some results on cyclic interval edge colorings of graphs

A proper edge coloring of a graph G with colors is called a cyclic interval t‐coloring if for each vertex v of G the edges incident to v are colored by consecutive colors, under the condition that color 1 is considered as consecutive to color t. We prove that a bipartite graph G of even maximum degree admits a cyclic interval ‐coloring if for every vertex v the degree satisfies either or . We also prove that every Eulerian bipartite graph G with maximum degree at most eight has a cyclic interval coloring. Some results are obtained for ‐biregular graphs, that is, bipartite graphs with the vertices in one part all having degree a and the vertices in the other part all having degree b; it has been conjectured that all these have cyclic interval colorings. We show that all (4, 7)‐biregular graphs as well as all ‐biregular () graphs have cyclic interval colorings. Finally, we prove that all complete multipartite graphs admit cyclic interval colorings; this proves a conjecture of Petrosyan and Mkhitaryan.     

Adjacency matrices of probe interval graphs

In this paper we obtain several characterizations of the adjacency matrix of a probe interval graph. In course of this study we describe an easy method of obtaining interval representation of an interval bigraph from its adjacency matrix. Finally, we note that if we add a loop at every probe vertex of a probe interval graph, then the Ferrers dimension of the corresponding symmetric bipartite graph is at most 3.     

Recognizing and representing proper interval graphs in parallel using merging and sorting

We present a parallel algorithm for recognizing and representing a proper interval graph in time with O(m+n) processors on the CREW PRAM, where m and n are the number of edges and vertices in the graph. The algorithm uses sorting to compute a weak linear ordering of the vertices, from which an interval representation is easily obtained. It is simple, uses no complex data structures, and extends ideas from an optimal sequential algorithm for recognizing and representing a proper interval graph [X. Deng, P. Hell, J. Huang, Linear-time representation algorithms for proper circular-arc graphs and proper interval graphs, SIAM J. Comput. 25 (2) (1996) 390-403].     

A dynamic distributed approach to representing proper interval graphs

First studied by Brodal and Fagerberg [G.S. Brodal, R. Fagerberg, Dynamic representation of sparse graphs, in: Algorithms and Data Structures, Proceedings of the 6th International Workshop, Vancouver, Canada, in: Lecture Notes in Computer Science, vol. 1663, Springer-Verlag, 1999], a dynamic adjacency labelling scheme labels the vertices of a graph so that the adjacency of two vertices can be deduced from their labels. The scheme is dynamic in the sense that only a small adjustment must be made to the vertex labels when a small change is made to the graph.Using a centralized dynamic representation of Hell, Shamir and Sharan [P. Hell, R. Shamir, R. Sharan, A fully dynamic algorithm for recognizing and representing proper interval graphs, SIAM Journal on Computing 31 (1) (2001) 289-305], we develop a bit/label dynamic adjacency labelling scheme for proper interval graphs. Our fully dynamic scheme handles vertex deletion/addition and edge deletion/addition in time. Furthermore, our dynamic scheme is error-detecting, as it recognizes when the new graph is not a proper interval graph.     

A characterization of cycle-free unit probe interval graphs

A graph is a probe interval graph (PIG) if its vertices can be partitioned into probes and nonprobes with an interval assigned to each vertex so that vertices are adjacent if and only if their corresponding intervals overlap and at least one of them is a probe. PIGs are a generalization of interval graphs introduced by Zhang for an application concerning the physical mapping of DNA in the human genome project. PIGs have been characterized in the cycle-free case by Sheng, and other miscellaneous results are given by McMorris, Wang, and Zhang. Johnson and Spinrad give a polynomial time recognition algorithm for when the partition of vertices into probes and nonprobes is given. The complexity for the general recognition problem is not known. Here, we restrict attention to the case where all intervals have the same length, that is, we study the unit probe interval graphs and characterize the cycle-free graphs that are unit probe interval graphs via a list of forbidden induced subgraphs.     

A maximal zero-free interval for chromatic polynomials of bipartite planar graphs

It is well known that (-∞,0) and (0,1) are two maximal zero-free intervals for all chromatic polynomials. Jackson [A zero-free interval for chromatic polynomials of graphs, Combin. Probab. Comput. 2 (1993), 325-336] discovered that is another maximal zero-free interval for all chromatic polynomials. In this note, we show that is actually a maximal zero-free interval for the chromatic polynomials of bipartite planar graphs.