单圈图的最大特征值序

主要讨论了单圈图按其最大特征值进行排序的问题，确定了该序的前六个图。     

最大2-正则诱导子图的长度

设G是2-连通图，c(G)是图G的最长诱导圈的长度，c′(G)是图G的最长诱导2-正则子图的长度。本文我们用图的特征值给出了c(G)和c′(G)的几个上界。     

强色指数的一个新的上界

给出了图的强色指数的一个新的上界，并指出几类恰好达到该上界的图，从而改进了Erodoes和Nesetri的强色指数猜想，在某种意义上证明了这个猜想。     

Fully-angular polyhex chains with minimal total π-electron energy

By Hückel molecular orbital (HMO) theory, the calculation of the total energy of all π-electrons in conjugated hydrocarbons can be reduced to that of E(G)=|λ₁|+|λ₂|+?+|λn|, where λi are the eigenvalues of the corresponding graph G. Denote by Ψn the set of all fully-angular polyhex chains with n hexagons. In this paper, we show that Hn has the minimum total π-electron energy among chains in Ψn, where Hn is the helicene chain.     

Diameter graphs of polygons and the proof of a conjecture of Graham

We show that for an n-gon with unit diameter to have maximum area, its diameter graph must contain a cycle, and we derive an isodiametric theorem for such n-gons in terms of the length of the cycle. We then apply this theorem to prove Graham's 1975 conjecture that the diameter graph of a maximal 2m-gon (m?3) must be a cycle of length 2m−1 with one additional edge attached to it.     

最大度为6的极大外平面图的完备色数

证明了最大度为６的极大外平面图的完备色数为７。     

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.