网络最小树的一种矩阵算法

求网络最小树问题，人们熟知常用的方法有“避圈法”和“破圈法”，这些方法有其直观易解的优点，然而它们毕竟是要在图上作业（在图上完成）。由于网络与距离矩阵的对应关系，本文将利用矩阵性质给出该问题的一个矩阵解法。     

次最小树及其相关问题-算法设计和复杂性分析

支撑树问题已经有很长的研究历史了,见[1].在许多工程问题中,需要产生一个网络G的所有支撑树,见[2,3,4].当G为赋权图时,每棵支撑树T有长度L（T）.在产生G的所有支撑树时,许多工程问题希望按照L（T）的非降顺序产生,见[5,6].在按照L（T）的非降顺序产生的支撑树中,有许多支撑树长度是相同的,而支撑树的数目又非常大（可以高达nn-2个）,因此算法的计算量非常大.本文希望能够按照L（T）的严格上升顺序产生所有的支撑树,从而避免大量的重复计算.     

系列平行图上带时间约束的Steiner最小树问题

对一类特殊系列平行图上带有时间约束的Steiner最小树问题,证明了其复杂性为NPC,并给出了一个完全多项式时间近似方案.     

具有最大Wiener—Hosoya指标的直径为d的Spider

M．Randic首先引入了Wiener．Hosoya指标，该指标可用于对分子的结构，性质和活跃性等方面进行研究．有且仅有一个顶点的度大于或等于3的树称为spider．本文对直径为d，且具有最大Wiener-Hosoya指标的spider进行了刻划．     

三维欧氏Steiner最小树的Delaunay四面体网格混合智能算法

Steiner最小树问题是组合优化中经典的NP难题,在许多实际问题中有着广泛的应用,而三维欧氏Steiner最小树问题是对二维欧氏Steiner最小树问题的推广。由于三维欧氏Steiner树问题的求解非常困难,至今为止的相关成果较为少见。本文针对该问题,利用Delaunay四面体网格剖分技术,提出了一种混合型智能求解方法,不仅可以尽量避免拓扑结构陷入局部最优,且对较大规模的问题求解亦有良好的效果。算法在Matlab环境下编程实现,经实例测试,获得了满意的效果。     

试卷质量评价指标区度的最化方法

本文分析了试卷质量评价指标区分度的概念及其量化方法，提出了一种更合理的最化方法。     

最小树的层次算法及全部最小树动态结构

最小树问题在国民经济中有着广泛的应用。本文提出不同于著名的kruskal算法[1]及其他算法的层次算法,并推导出揭示最小树不变量的枝杈确定性以及边可作为最小树树枝的充要条件,最后得出全部最小树的动态结构。由于实际选用最小树时还经常需要兼顾其它具体     

最小树图的Hamilton性及全部最小树的生成

对给定的连通图G,树图T(G)的Hamilton性,首先由Cummins所证明。稍后,Kamae给出另一构造证明,并用于树的生成。本文将研究一个赋权图G所有最小树的一些性质。主要结果如下:(1)对任意赋权图G,证明了最小树图T_(min)(G)的Hamilton性;(2)根据构造性证明,给出生成全部最小树的算法。     

最小树的一般算法

本文根据设计并行算法的基本原则,给出了最小树的两个对偶定理.在此基础上,建立了两种对偶的同步并行算法的雏型.这两种算法恰恰在对偶的意义下,概括了以往的最小树算法.     

具有最小反对称分割指数的化学树

设图$G$,其中边集为$E(G)$,顶点集$V(G)$.反对称分割指数被定义为$ISDD(G)=\sum_{uv \in E(G)}\dfrac{d_ud_v}{d_u^2+d_v^2}$,其中$d_u$, $d_v$分别为顶点$u,v$的度.化学树就是顶点的度不超过4的树.在本文中,我们刻画出具有最小反对称分割指数的$n$阶化学树.     

关于乘积Sombor指数的极值(分子)树

拓扑指数是一类可以用来预测化合物的物理化学性质的数值不变量, 其并被广泛用于量子化学、分子生物学和其他研究领域. 对于一个顶点集为$V(G)$、边集为$E(G)$的(分子)图$G$, 其Sombor指数定义为$SO(G)=\sum\limits_{uv\in E(G)}\sqrt{d_{G}^{2}(u)+d_{G}^{2}(v)}$, 其中$d_{G}(u)$表示顶点$u$在$G$中的度. 相应地, 乘积Sombor指数定义为$\prod\nolimits_{SO}(G)= \prod\limits_{uv\in E(G)}\sqrt{d_{G}^{2}(u)+d_{G}^{2}(v)}$. 分子树是最大度$\Delta\leq 4$的树. 在本文中, 我们首先确定了乘积Sombor指数最大的分子树, 然后我们确定了乘积Sombor指数的前十三小的(分子)树.     

On Minimum Edge Ranking Spanning Trees

In this paper, we introduce the problem of computing a minimum edge ranking spanning tree (MERST); i.e., find a spanning tree of a given graph G whose edge ranking is minimum. Although the minimum edge ranking of a given tree can be computed in polynomial time, we show that problem MERST is NP-hard. Furthermore, we present an approximation algorithm for MERST, which realizes its worst case performance ratio where n is the number of vertices in G and Δ* is the maximum degree of a spanning tree whose maximum degree is minimum. Although the approximation algorithm is a combination of two existing algorithms for the restricted spanning tree problem and for the minimum edge ranking problem of trees, the analysis is based on novel properties of the edge ranking of trees.     

Trees with Given Diameter Minimizing the Augmented Zagreb Index and Maximizing the ABC Index

Let G be a simple connected graph with vertex set V(G) and edge set E(G).The augmented Zagreb index of a graph G is defined asAZI(G) =∑uv∈E(G)(d_ud_v/(d_u + d_v-2))~3,and the atom-bond connectivity index(ABC index for short) of a graph G is defined asABC(G) =∑uv∈E(G)((d_u + d_v-2)/d_ud_v),where d_u and d_v denote the degree of vertices u and v in G,respectively.In this paper,trees with given diameter minimizing the augmented Zagreb index and maximizing the ABC index are determined,respectively.     

固定直径的树的Wiener指数

图G的wiener指数定义为图中所有点对u,v的距离之和∑d（u,v）. 在这篇文章中,我们刻画了在n个顶点直径为d的所有树中具有第三小wiener指数的树的特征以及介绍了得到这类树的wiener指数排序的方法.     

最大Randid指标的k悬挂点化学树的性质

化学分子图G的Randie指标为R（G）=∑wv（dG（u）dG（v））^2/1．其中uv是G的边,dG（u）表示的顶点u的度．本文刻画了具有最大Randie指标的k悬挂点化学树的一些性质．     

Minimum Spanning Trees with Sums of Ratios

We present an algorithm for finding a minimum spanning tree where the costs are the sum of two linear ratios. We show how upper and lower bounds may be quickly generated. By associating each ratio value with a new variable in `image space,' we show how to tighten these bounds by optimally solving a sequence of constrained minimum spanning tree problems. The resulting iterative algorithm then finds the globally optimal solution. Two procedures are presented to speed up the basic algorithm. One relies on the structure of the problem to find a locally optimal solution while the other is independent of the problem structure. Both are shown to be effective in reducing the computational effort. Numerical results are presented.     

最大Randi(c)指标的k悬挂点化学树的性质

化学分子图G的Randic指标为R(G)=E(dG(u)dG(v))-(1/2).其中uv是G的边,dG(u)表示G的顶点u的度.本文刻画了具有最大Randic指标的K悬挂点化学树的一些性质.     

Local Minimum Principle for Optimal Control Problems Subject to Differential-Algebraic Equations of Index Two

Necessary conditions in terms of a local minimum principle are derived for optimal control problems subject to index-2 differential-algebraic equations, pure state constraints, and mixed control-state constraints. Differential-algebraic equations are composite systems of differential equations and algebraic equations, which arise frequently in practical applications. The local minimum principle is based on the necessary optimality conditions for general infinite optimization problems. The special structure of the optimal control problem under consideration is exploited and allows us to obtain more regular representations for the multipliers involved. An additional Mangasarian-Fromowitz-like constraint qualification for the optimal control problem ensures the regularity of a local minimum. An illustrative example completes the article.The author thanks the referees for careful reading and helpful suggestions and comments.     

Comparison of Algorithms for the Degree Constrained Minimum Spanning Tree

The Degree Constrained Minimum Spanning Tree (DCMST) on a graph is the problem of generating a minimum spanning tree with constraints on the number of arcs that can be incident to vertices of the graph. In this paper we develop three heuristics for the DCMST, including simulated annealing, a genetic algorithm and a method based on problem space search. We propose alternative tree representations to facilitate the neighbourhood searches for the genetic algorithm. The tree representation that we use for the genetic algorithm can be generalised to other tree optimisation problems as well. We compare the computational performance of all of these approaches against the performance of an exact solution approach in the literature. In addition, we also develop a new exact solution approach based on the combinatorial structure of the problem. We test all of these approaches using standard problems taken from the literature and some new test problems that we generate.