一种具有平均累积优势度的排序方法

本文结合特征向量法（EM）及和法（SM）优点,提出了一种新的排序方法一具有平均累积优势度的和法（DSM）,同EM,SM,MDM[6]相比,此法简单,实用,可靠,计算权重所需时间少,且与EM总量得到相同的方案排序,而其它方法如平均优势度矩阵法（MDM）,对数最小二乘法（LISM）,最小偏差法（LDM）有时会产生逆序。     

AHP中计算排序向量的优势度矩阵法

本将优势度矩阵与最小夹角法（LAM）的相对熵方法（REM）相结合，提出了两种新的计算排序向量的方法——优势度最小夹角法（DLAM）和优势度相对熵方法（DREM），并讨论了它们的性质。理论研究和算例分析都表明，这是两种比较好的计算排序向量的方法。     

层次分析中广义最小偏差法的性质

广义最小偏差法（GLDM）是层次分析中一种重要的排序方法．本文讨论了广义最小偏差法的性质和灵敏度分析问题．     

模糊环境下的一种多准则决策方法

本文利用模糊集理论以及层次分析法（AHP）原理，建立了一种在模糊环境下对方案进行择优或排序的多准则决策方法。     

Johnson法则在成组加工排序中的推广

成组技术（Group Technology）是把工件分组进行加工,以提高生产效率的一种生产组织方法,本文把两台机器同序作业（同顺序流水作业）排序问题F2│perm│C_(max)的John-son法则推广到成组加工上,提出确定组与组之间顺序的最优法则,给出了这个问题成组加工的最优排法,并分析算法的计算复杂性。     

基于删失数据的指数威布尔分布最大似然估计的新算法

本文讨论了指数威布尔分布当观测数据是删失数据情形时参数的最大似然估计问题.因为删失数据是一种不完全数据,我们利用EM算法来计算参数的近似最大似然估计.由于EM算法计算的复杂性,计算效率也不理想.为了克服牛顿-拉普森算法和EM算法的局限性,我们提出了一种新的方法.这种方法联合了指数威布尔分布到指数分布的变换和等效寿命数据的技巧,比牛顿-拉普森算法和EM算法更具有操作性.数据模拟讨论了这一方法的可行性.为了演示本文的方法,我们还提供了一个真实寿命数据分析的例子.     

三角模糊数直觉模糊PA算子及其应用

针对决策信息为三角模糊数直觉模糊数（TFNIFN）且属性间存在相互关联的多属性群决策（MAGDM）问题,提出了一种基于三角模糊数直觉模糊PA （TFNIFPA）算子的决策方法.首先,基于TFNIFN的运算法则和PA （Power Average）算子,定义了TFNIFPA算子.然后,研究了该算子的一些性质,建立基于TFNIFPA算子的MAGDM模型,结合排序方法进行决策.最后通过MAGDM算例验证了该算子的有效性与可行性.     

加工时间依赖于机器的自由作业排序问题

1992年M．Dror提出工件的加工时间依赖于机器的排序问题（schedulingwithmachinedependentprocessingtimes），并研究以最大完工时间（makespan）和以总的完工时间为优化目标的两种这类排序问题．然而，M．Dror对以总的完工时间为优化目标提出的“最优算法”是错误的．本文用算例表明他提出的算法不是最优的，并在机器连续加工的条件下，把这个排序问题转化成指派问题（assignmentproblem），从而可以用匈牙利算法得到最优解．最后，我们提出几个尚未解决的问题，以期引起国内外同行进一步研究．     

不完全信息下多目标决策的一种新方法

基于部分偏好信息（目标权重）,本提出了多目标决策的一种线性规划算法,该法避免了获取偏好信息的困难,在较少信息下,为决策提供更普遍,易操作且有效的方案排序结果。最后进行了算例分析。     

基于Erdos1合著网络和论文引用网络的复杂网络节点特征研究

首先,研究了Erdos1合著网络的特征属性,一方面使用节点的度、介数、接近中心性来描述Erdos1合著网络节点重要性,另一方面使用特征向量中心性和本文提出的高阶度参数来描述Erdos1合著网络节点影响力;然后,分别用逼近理想解的排序算法（TOPSIS算法）和主成份分析（PCA）对节点重要性和影响力排序;最后,利用修改的网页排名算法（PageRank算法）讨论了网络科学原创性论文中最具影响力的论文。     

双边定时截尾样本下广义逆指数分布形状参数的估计

先给出了广义逆指数分布在双边定时截尾样本下形状参数的最大似然估计,并不能得到估计的显式表达式,但证明了参数在(0,+∞)上最大似然估计是唯一存在的.其次提出用EM算法求出形状参数的估计且该估计具有良好的收敛性,还给出了形状参数的EM估计的渐近方差和近似置信区间;最后通过数值模拟,对形状参数的最大似然估计和EM估计的效果进行了比较,说明了用EM算法求形状参数的估计是可行的,并且模拟效果相对比较好.     

A new method for solving Pareto eigenvalue complementarity problems

In this paper, we introduce a new method, called the Lattice Projection Method (LPM), for solving eigenvalue complementarity problems. The original problem is reformulated to find the roots of a nonsmooth function. A semismooth Newton type method is then applied to approximate the eigenvalues and eigenvectors of the complementarity problems. The LPM is compared to SNM_min and SNM_FB, two methods widely discussed in the literature for solving nonlinear complementarity problems, by using the performance profiles as a comparing tool (Dolan, Moré in Math. Program. 91:201–213, 2002). The performance measures, used to analyze the three solvers on a set of matrices mostly taken from the Matrix Market (Boisvert et al. in The quality of numerical software: assessment and enhancement, pp. 125–137, 1997), are computing time, number of iterations, number of failures and maximum number of solutions found by each solver. The numerical experiments highlight the efficiency of the LPM and show that it is a promising method for solving eigenvalue complementarity problems. Finally, Pareto bi-eigenvalue complementarity problems were solved numerically as an application to confirm the efficiency of our method.     

一类随机泛函微分方程带随机步长的EM逼近的渐近稳定

研究了一类带有限延迟的随机泛函微分方程的Euler-Maruyama(EM)逼近，给出了该方程的带随机步长的EM算法，得到了随机步长的两个特点:首先，有限个步长求和是停时；其次，可列无限多个步长求和是发散的.最终，由离散形式的非负半鞅收敛定理，得到了在系数满足局部Lipschitz条件和单调条件下，带随机步长的EM数值解几乎处处收敛到0.该文拓展了2017年毛学荣关于无延迟的随机微分方程带随机步长EM数值解的结果.     

Proper minimal points of nonconvex sets in Banach spaces in terms of the limiting normal cone

In this paper, proper minimal elements of a given nonconvex set in a real ordered Banach space are defined utilizing the limiting (Mordukhovich) normal cone. The newly defined points are called limiting proper minimal (LPM) points. It is proved that each LPM is a proper minimal in the sense of Borwein under some assumptions. The converse holds in Asplund spaces. The relation of LPM points with Benson, Henig, super and proximal proper minimal points are established. Under appropriate assumptions, it is proved that the set of robust elements is a subset of the set of LPM points, and the set of LPM points is dense in that of minimal points. Another part of the paper is devoted to scalarization-based and distance function-based characterizations of the LPM points. The paper is closed by some results about LPM solutions of a set-valued optimization problem via variational analysis tools. Clarifying examples are given in addition to the theoretical results.     

Linear programming in measure spaces

This paper studies a linear programming problem in measure spaces (LPM). Several results are obtained. First, the optimal value of LPM can be equal to the optimal value of the dual problem (DLPM), but the solution of DLPM may be not exist in its feasible region. Sccond, :he relations between the optimal solution of LPM and the extreme point of the feasible region of LPM are discussed. In order to investigate the conditions under which a feasible solution becomes an extremal point, the inequality constraint of LPM is transformed to an equality constraint. Third, the LPM can be reformulated to be a general capacity problem (GCAP) or a linear semi-infinite programming problem (LSIP = SIP), and under appropriate restrictioiis, the algorithm developed by the authors in [7] and [8] are applicable for developing an approximation scheme for the optimal solution of LPM     

A Hybrid of the Newton-GMRES and Electromagnetic Meta-Heuristic Methods for Solving Systems of Nonlinear Equations

Solving systems of nonlinear equations is perhaps one of the most difficult problems in all numerical computation. Although numerous methods have been developed to attack this class of numerical problems, one of the simplest and oldest methods, Newton’s method is arguably the most commonly used. As is well known, the convergence and performance characteristics of Newton’s method can be highly sensitive to the initial guess of the solution supplied to the method. In this paper a hybrid scheme is proposed, in which the Electromagnetic Meta-Heuristic method (EM) is used to supply a good initial guess of the solution to the finite difference version of the Newton-GMRES method (NG) for solving a system of nonlinear equations. Numerical examples are given in order to compare the performance of the hybrid of the EM and NG methods. Empirical results show that the proposed method is an efficient approach for solving systems of nonlinear equations.     

Modelling lumped-parameter sorption kinetics and diffusion dynamics of odour-causing VOCs to dust particles

An analytical algorithm is presented for fast simulation of the adsorption kinetics and diffusion dynamics of odour-causing volatile organic compounds (VOC-odour) which originate in the stored swine manure to airborne dust particles in a ventilated airspace. The model is an extension to the well-known lumped-parameter model (LPM) that incorporates a Langmuir–Hinshelwood (LH) kinetic concept dependent on VOC-odour concentration with diffusion limitation. The basic idea behind the model implementation is to couple the calculations of the two major processes in the VOC-odour/dust particle system: VOC-odour diffusion based on the homogeneous surface diffusion model (HSDM) and surface reaction based on the LH kinetics in an LPM scheme. The LPM employs Laplace transforms and gamma distributions of the rate coefficient to produce a lumped-parameter gamma model (LPGM) for kinetic equation of VOC-odour adsorption to airborne dust particles, whereas the HSDM incorporates the age and size distributions of airborne dust for evaluating the dust-borne VOC-odour dynamics. The integrate assessment of VOC-odour sorption kinetics and diffusion dynamics allows to relate the adsorption rate coefficient, reaction order, and surface effective diffusivity in a complex VOC-odour/dust particle system. The LPGM fitted well with the data obtained numerically from HSDM and successfully determined the adsorption rate coefficient and reaction order for each sorption process.     

Corrective meshless particle formulations for time domain Maxwell''s equations

In this paper a meshless approximation of electromagnetic (EM) field functions and relative differential operators based on particle formulation is proposed. The idea is to obtain numerical solutions for EM problems by passing up the mesh generation usually required to compute derivatives, and by employing a set of particles arbitrarily placed in the problem domain. The meshless Smoothed Particle Hydrodynamics method has been reformulated for solving the time domain Maxwell's curl equations. The consistency of the discretized model is investigated and improvements in the approximation are obtained by modifying the numerical process. Corrective algorithms preserving meshless consistency are presented and successfully used. Test problems, dealing with even and uneven particles distribution, are simulated to validate the proposed methodology, also by introducing a comparison with analytical solution.     

Computationally Efficient Estimation for the Generalized Odds Rate Mixture Cure Model With Interval-Censored Data

For semiparametric survival models with interval-censored data and a cure fraction, it is often difficult to derive nonparametric maximum likelihood estimation due to the challenge in maximizing the complex likelihood function. In this article, we propose a computationally efficient EM algorithm, facilitated by a gamma-Poisson data augmentation, for maximum likelihood estimation in a class of generalized odds rate mixture cure (GORMC) models with interval-censored data. The gamma-Poisson data augmentation greatly simplifies the EM estimation and enhances the convergence speed of the EM algorithm. The empirical properties of the proposed method are examined through extensive simulation studies and compared with numerical maximum likelihood estimates. An R package “GORCure” is developed to implement the proposed method and its use is illustrated by an application to the Aerobic Center Longitudinal Study dataset. Supplementary material for this article is available online.