w-DENSITY AND w-BALANCED PROPERTY OF WEIGHTED GRAPHS

§ 1　IntroductionAll graphsconsidered in this paperare finite undirected ones withoutloops ormultipleedges.Our terminology and notation are standard exceptas indicated.A good reference forany undefined terms is[1 ] .Let G be a graph with vertex set V( G) and edge set E( G) .The density of G is definedbyd( G) =ε( G)ν( G) ,whereν( G) andε( G) denote| V( G) | and| E( G) | ,respectively.G is said to be balanced iffor each subgraph H of G we have d( H )≤ d( G) ,where V( H ) is assum…     

Bager第五图的完善

１９８９年发表的Ｂａｇｅｒ第五图，包含关于三角形元素的３５个二次规范画数之间的５１个不等式通过细致的分析，本文给出了其中遗漏的１２个基本不等式     

一类几乎最优循环图{C_p(m,m+1,p/a)}

本文比较了循环图类{c_p(n_1,…,n_p)}和{c-p(n_1…,n_p,p/α)}的直径下界。对于p和α满足一定条件的循环图类{c_p(n_1,n_2,p/α)},本文给出了达到或几乎达到此图类直径下界的一类几乎最优循环图{c_p(m,m+1,p/α)}。     

Combinatorial Optimization by Dynamic Contraction

A heuristic optimization methodology, Dynamic Contraction (DC), is introduced as an approach for solving a wide variety of hard combinatorial problems. Contraction is an operation that maps an instance of a problem to a smaller instance of the same problem. DC is an iterative improvement strategy that relies on contraction as a mechanism for escaping local minima. As a byproduct of contraction, efficiency is improved due to a reduction of problem size. Effectiveness of DC is shown through simple applications to two classical combinatorial problems: The graph bisection problem and the traveling salesman problem.     

Coarsely Invariant Hilbert Spaces over Infinite Connected Graphs

We study in this paper a Hilbert space HV associated with the coarse geometry of an infinite connected graph X(V,E) with vertex set V and edge set E. We show that X( V, E) is uniformly expanding if and only if l2( V) can be continuously included in HV as a closed subspace, and that the inner product structure of HV is topologically invariant under uniform coarsening of the graph. We also discuss the functorial properties of these Hilbert spaces.     

A graph theory approach to subcontracting, machine duplication and intercell moves in cellular manufacturing

We address in this paper the problem of finding an optimal strategy for dealing with bottleneck machines and bottleneck parts in the cell formation process in group technology. Three types of economic decisions are considered: subcontracting, machine duplication and intercell moves. The problem is formulated as a minimum weighted node covering problem in a hypergraph, and we show that it can be solved in polynomial time by finding a maximum weighted stable set in a bipartite graph. We extend this result to cellular manufacturing systems in which the sequence of operations of each part is known in advance.     

关于三次图边可重构问题的注记

对δ（Ｇ）≥８的连续三次图Ｇ是边可重构的定理给出了一个简单证明。此外还证明了，当δ（Ｇ）＝７，γ（Ｇ）≤８２以及δ（Ｇ）＝６，γ（Ｇ）≤１７时，连续三次图Ｇ是边可重构的     

Some Recent Progress and Applications in Graph Minor Theory

In the core of the seminal Graph Minor Theory of Robertson and Seymour lies a powerful theorem capturing the ``rough' structure of graphs excluding a fixed minor. This result was used to prove Wagner's Conjecture that finite graphs are well-quasi-ordered under the graph minor relation. Recently, a number of beautiful results that use this structural result have appeared. Some of these along with some other recent advances on graph minors are surveyed. Research partly supported by Japan Society for the Promotion of Science, Grant-in-Aid for Scientific Research, Grant number 16740044, by Sumitomo Foundation, by C & C Foundation and by Inoue Research Award for Young Scientists Supported in part by the Research Grant P1–0297 and by the CRC program On leave from: IMFM & FMF, Department of Mathematics, University of Ljubljana, Ljubljana, Slovenia     

Gk^d图的平面性和平面图的色数

利用欧拉公式研究了Gdk图的平面性,获得了一个重要定理,并由此得到了关于平面图色数的一个结论.     

Clustering of spectra and fractals of regular graphs

We exhibit a characteristic structure of the class of all regular graphs of degree d that stems from the spectra of their adjacency matrices. The structure has a fractal threadlike appearance. Points with coordinates given by the mean and variance of the exponentials of graph eigenvalues cluster around a line segment that we call a filar. Zooming-in reveals that this cluster splits into smaller segments (filars) labeled by the number of triangles in graphs. Further zooming-in shows that the smaller filars split into subfilars labeled by the number of quadrangles in graphs, etc. We call this fractal structure, discovered in a numerical experiment, a multifilar structure. We also provide a mathematical explanation of this phenomenon based on the Ihara-Selberg trace formula, and compute the coordinates and slopes of all filars in terms of Bessel functions of the first kind.