基于邻域信息的社区发现方法

考虑含有节点邻域信息的新模块度函数的社区发现方法和最优分组下标度参数的选择问题,通过谱松弛方法求解模块度函数的最大化问题,最终利用新算法快速求解,并通过真实网络数据验证算法能更好的发现社区.     

广义Nekrasov矩阵的判别法及其迭代算法

对任意给定矩阵,通过对其行下标集不同的递进式划分,结合不等式的放缩技巧,给出广义Nekrasov矩阵的若干判别法,并进而获得广义Nekrasov矩阵的迭代算法,改进和推广了已有相关结果.     

广义Nekrasov矩阵的判别法及其迭代算法北大核心

对任意给定矩阵,通过对其行下标集不同的递进式划分,结合不等式的放缩技巧,给出广义Nekrasov矩阵的若干判别法,并进而获得广义Nekrasov矩阵的迭代算法,改进和推广了已有相关结果.     

A mathematical analysis for a diffusive epidemic model with criss-cross dynamics

Abstract. In this paper, an initial boundary value problem with homogeneous Neumann bound-ary condition is studied for a reaction diffusion system which models the spread of infectious dis-eases within two population groups by means of serf and criss-cross infection mechanism, Exis-tence, uniqueness and houndedness of the nonnegative global solution     

Superconvergence and asymptotic expansions for linear finite element approximations on criss-cross mesh

In this paper, we discuss the error estimation of the linear finite element solution on criss-cross mesh. Using space orthogonal decomposition techniques, we obtain an asymptotic expansion and superconvergence results of the finite element solution. We first prove that the asymptotic expansion has different forms on the two kinds of nodes and then derive a high accuracy combination formula of the approximate derivatives.     

具有混合型边界条件的左定Sturm-Liouville问题特征值的下标计算(英文)

本文研究具有混合型边界条件的左定Sturm-Liouvile问题特征值的下标计算问题.首先给出具有分离型边界条件和混合型边界条件的左定Sturm-Liouville问题的特征值之间的不等式;然后利用这个结果给出一种计算混合型边界条件下左定Sturm-Liouville问题特征值下标的方法.     

A GENERAL DETERMINISTIC PIVOT METHOD FOR ORIENTED MATROID PROGRAMMING

A new pivot method for oriented matroid progiamming is given out. This mathod is deterministic by nature and is general in the sense that its flexible pivot selection rule allows a family of possible algorithms to be its special cases, including the so called criss-cross algorithm and the Edmonds-Fukuda algorithm as well. As an example of a special implementation of our general method, an extended version of the Edmonds-Fukuda algorithm is presented.     

串行运算向量化的下标追踪法

本文为电子计算机向量运算识别器研制了一种识别与构造算法,这种算法自成体系,被命名为“下标追踪法”。跟坐标方法和时性关系矩阵方法相比较,它不仅增强了对于赋值语句循环的识别能力,而且把识别范围扩张到IF与GOTO语句,正在诸如151-3/4大型序列机一类的系统上加以实施。 文中介绍下标追踪法的基本思想、基本理论和基本方法,主要提出构造时序层次的公理系统——繁衍规则,证明了年长顺序定理与判别准则。     

关于包含奇-偶下标第二类契贝谢夫多项式的恒等式

给出了一类包含偶下标第二类契贝谢夫多项式和一类包含奇下标第二类契贝谢夫多项式求和的递推公式，得到了一些包含偶下标第二类契贝谢夫多项式和奇下标第二类契贝谢夫多项式的恒等式．     

正Fibonacci数的标准分解式中因子5的指数

根据Fibonacci数列的定义,利用初等数论的知识和数学归纳法,讨论了正Fibonacci数Fn的标准分解式中因子5的指数与下标n的关系,得到下列结论:正Fibonacci数Fn的标准分解式中因子5的指数,与下标n的标准分解式中因子5的指数一致.     

线性互补问题的宽邻域预估校正算法

对线性互补问题提出了一种新的宽邻域预估校正算法,算法是基于经典线性规划路径跟踪算法的思想,将Maziar Salahi关于线性规划预估校正算法推广到线性互补问题中,给出了算法的具体迭代步骤并讨论了算法迭代复杂性,最后证明了算法具有多项式复杂性为O(ηlog(X~0)~Ts~0/ε)。     

Sequential Systems of Linear Equations Algorithm for Nonlinear Optimization Problems with General Constraints

In Ref. 1, a new superlinearly convergent algorithm of sequential systems of linear equations (SSLE) for nonlinear optimization problems with inequality constraints was proposed. At each iteration, this new algorithm only needs to solve four systems of linear equations having the same coefficient matrix, which is much less than the amount of computation required for existing SQP algorithms. Moreover, unlike the quadratic programming subproblems of the SQP algorithms (which may not have a solution), the subproblems of the SSLE algorithm are always solvable. In Ref. 2, it is shown that the new algorithm can also be used to deal with nonlinear optimization problems having both equality and inequality constraints, by solving an auxiliary problem. But the algorithm of Ref. 2 has to perform a pivoting operation to adjust the penalty parameter per iteration. In this paper, we improve the work of Ref. 2 and present a new algorithm of sequential systems of linear equations for general nonlinear optimization problems. This new algorithm preserves the advantages of the SSLE algorithms, while at the same time overcoming the aforementioned shortcomings. Some numerical results are also reported.     

A search algorithm for linear codes: progressive dimension growth

This paper presents an algorithm, called progressive dimension growth (PDG), for the construction of linear codes with a pre-specified length and a minimum distance. A number of new linear codes over GF(5) that have been discovered via this algorithm are also presented.      

一个新的求解线性规划最小二乘算法

§1Introduction Currently,therearetwopopularapproachesinlinearprogramming:pivotalgorithm andinterior-pointalgorithm.Manyoftheirvariantsdevelopedbothintheoryand applicationsarestillinprogress.Thepivotmethodobtainstheoptimalsolutionviamoving consecutivelytoabettercorner-pointinthefeasibleregion,anditsmodificationstryto improvethespeedofattainingtheoptimality.Incontrast,theinterior-pointalgorithmis claimedasaninterior-pointapproach,whichgoesfromafeasiblepointtoafeasiblepoint throughtheinterioroft…     

An infeasible nonmonotone SSLE algorithm for nonlinear programming

In this paper, we propose a new nonmonotone algorithm using the sequential systems of linear equations, which is an infeasible QP-free method. We use neither a penalty function nor a filter. Therefore, it is unnecessary to choose a problematic penalty parameter. The new algorithm only needs to solve three systems of linear equations with the same nonsingular coefficient matrix. Under some suitable conditions, the global convergence is established. Some numerical results are also presented.     

二分单纯形算法中子规划问题的进一步研究

本对二分单纯形算法的子规划问题作进一步研究,提出一个新的子规划问题来改善问题的不可行性,并确定了相应的主元旋转规则,并编制了相应于新子规划的新二分算法,并对94个线性规划问题进行了数值实验,实验结果表明,新二分算法是一种改进的二分算法。     

一个新的单纯形类算法

提出了一个求解线性规划的新单纯形类算法。它不仅无须引入人工变量，而且在第一阶段中采用无比检验。因此新算法比Arsham最近提出的push-to—pull算法效率更高。此外，本算法的数值稳定性也优于push—to—pull算法。     

An O(n log n) algorithm for finding all repetitions in a string

Any nonempty string of the form xx is called a repetition. An O(n log n) algorithm is presented to find all repetitions in a string of lenght n. The algorithm is based on a linear algorithm to find all the new repetitions formed when two strings are concatenated. This linear algorithm is possible because new repetitions of equal length must occur in blocks with consecutive starting positions. The linear algorithm uses a variation of the Knuth-Morris-Pratt algorithm to find all partial occurrences of a pattern within a text string. It is also shown that no algorithm based on comparisons of symbols can improve O(n log n). Finally, some open problems and applications are suggested.     

Relaxation,New Combinatorial and Polynomial Algorithms for the Linear Feasibility Problem

We consider the homogenized linear feasibility problem, to find an x on the unit sphere satisfying n linear inequalities a_i ^Tx \ge 0. To solve this problem we consider the centers of the inspheres of spherical simplices, whose facets are determined by a subset of the constraints. As a result we find a new combinatorial algorithm for the linear feasibility problem. If we allow rescaling, this algorithm becomes polynomial. We point out that the algorithm also solves the more general convex feasibility problem. Moreover, numerical experiments show that the algorithm could be of practical interest.     

Primal and dual multi-objective linear programming algorithms for linear multiplicative programmes

Multiplicative programming problems (MPPs) are global optimization problems known to be NP-hard. In this paper, we employ algorithms developed to compute the entire set of nondominated points of multi-objective linear programmes (MOLPs) to solve linear MPPs. First, we improve our own objective space cut and bound algorithm for convex MPPs in the special case of linear MPPs by only solving one linear programme in each iteration, instead of two as the previous version indicates. We call this algorithm, which is based on Benson’s outer approximation algorithm for MOLPs, the primal objective space algorithm. Then, based on the dual variant of Benson’s algorithm, we propose a dual objective space algorithm for solving linear MPPs. The dual algorithm also requires solving only one linear programme in each iteration. We prove the correctness of the dual algorithm and use computational experiments comparing our algorithms to a recent global optimization algorithm for linear MPPs from the literature as well as two general global optimization solvers to demonstrate the superiority of the new algorithms in terms of computation time. Thus, we demonstrate that the use of multi-objective optimization techniques can be beneficial to solve difficult single objective global optimization problems.