NBU分布类的拟合优度检验

一个寿命分布F称为属于新的比旧的好的分布类(NBU),若: R(x y)≤R(x)R(y) x,y≥0这里R(x)=1-F(x)。若R(x y)≥R(x)R(y),称作旧的比新的好(NWU)。本文讨论可靠性中应用非常广泛的NBU分布类的检验问题,即下列检验问题:原假设H_0:F是NBU的。备选假设H_A:F不是NBU。给出了检验函数。并证明了备选假设是H_A:F是NWU时,检验是无偏的。     

年龄点t0之后的NBU性的非参数检验方法

NBU＊t0寿命分布中新元件的寿命随机地大于旧的年龄不小于t0的元件的剩余寿命,这为更广泛地模拟元件的老化和劣化现象提供了丰富的内容。本文首先对那些t0年龄点之后剩余寿命随机等于新元件寿命的元件的结构加以刻画,然后建立了一个非参数检验方法以区分这种随机等价性和t0年龄点后的严格的NBU性,并给出了针对一个NBU＊t0但非NBU的寿命分布的例子的数值模拟结果。     

检验在t0处F是否比G具有更强的NBU性

对NBU－t0元件在t0处的NBU性强弱提出了一个比较方法，并据此比较方法建立了一个基于U-统计量的对NBU性强弱的大子样非参数检验方法，同时对该检验的渐近无偏性及其性质作了探讨，并给出了一个更广泛的检验方法．     

近性Heyting代数

本文在有最小元0的Heyting代数上引入了对偶等价的(半)近性关系和(半)近性序的概念,它们是一般拓扑学中全正则空间上对偶等价的近性关系和近性序的合理推广.本文的工作弥补了Gierz和Keimel相应工作的缺陷,更正了他们的一个错误结果.     

关于DMRL序及其相关序的若干性质

证明了DMRL偏序关系在平移和尺度变换下的不变性,并获得了一个充分必要条件.同时考虑了DMRL序与IFR及IFRA序之间的关系.     

终极破产概率的双边界

本文对一类理赔额分布给出了Andersen风险过程终极破产概率的上、下界，并考查了理赔分布的平衡分布是NBU和NWU的破产概率的情况。     

编序式问卷调查的模糊偏序排序法

讨论了现有的编序式问卷调查排序方法的不足之处;提出了基于模糊偏序关系的编序式问卷调查的排序方法,给出了模糊偏序排序法的数学模型,论证了用模糊偏序关系对编序式问卷调查进行排序是一种较好的方法;并用实例分析了模糊偏序排序法应用于编序式问卷调查的具体操作步骤.     

(2χ~2)~(1/2)-(2n-1)~(1/2)的近似正态性及多总体标准差的齐性检验

计算了随机变量(2χ~2)~(1/2)的数学期望和方差,比较分析了随机变量(2χ~2)~(1/2)-2n~(1/2)与(2χ~2)~(1/2)-(2n-1)~(1/2)的近似分布的相同和不同之处,并且利用2χ2的近似分布的正态性,建立了多总体标准差的检验法.     

利用二阶上三角矩阵构造各类非交换的序群

利用二阶上三角矩阵分别构造了非交换的序群、拟序群、拟偏序群和拟格序群.     

关于Rees商超序半群

本文给出了Rees同余商超序半群的详细构造,将序半群上的Rees同余商半群推广到超序半群上.本文的主要结论是:设(S,.,≤)为超序半群,K是S的理想,记S | K:=(S\K)U{0},其中0是K中任一元素,那么存在S|K上的二元超运算*以及偏序关系(<)使得(S|K,*,(<))是一个超序半群.     

Aging properties of the residual life length of k‐out‐of‐n systems with independent but non‐identical components

The k‐out‐of‐n structure is a very popular type of redundancy in fault‐tolerant systems, it has founded wide applications in industrial and military systems during the past several decades. This paper will investigate the residual life length of a k‐out‐of‐n system with independent (not necessarily identical) components, given that the (n?k)th failure has occurred at time t?0. Behaviour of PF₂, IFR, DRHR, DMRL, NBU(2) and NBUC classes of life distributions are derived in terms of the monotonicity of the residual life given the time of the (n?k)th failure. Copyright © 2004 John Wiley & Sons, Ltd.     

Characterization of properly optimal elements with variable ordering structures

In vector optimization with a variable ordering structure, the partial ordering defined by a convex cone is replaced by a whole family of convex cones, one associated with each element of the space. In recent publications, it was started to develop a comprehensive theory for these vector optimization problems. Thereby, also notions of proper efficiency were generalized to variable ordering structures. In this paper, we study the relation between several types of proper optimality. We give scalarization results based on new functionals defined by elements from the dual cones which allow complete characterizations also in the nonconvex case.     

Fuzzy Optimization Problems Based on Ordering Cones

The solution concepts of the fuzzy optimization problems using ordering cone (convex cone) are proposed in this paper. We introduce an equivalence relation to partition the set of all fuzzy numbers into the equivalence classes. We then prove that this set of equivalence classes turns into a real vector space under the settings of vector addition and scalar multiplication. The notions of ordering cone and partial ordering on a vector space are essentially equivalent. Therefore, the optimality notions in the set of equivalence classes (in fact, a real vector space) can be naturally elicited by using the similar concept of Pareto optimal solution in vector optimization problems. Given an optimization problem with fuzzy coefficients, we introduce its corresponding (usual) optimization problem. Finally, we prove that the optimal solutions of its corresponding optimization problem are the Pareto optimal solutions of the original optimization problem with fuzzy coefficients.     

Mean residual life and increasing convex comparison of shock models

Two devices are subjected to shocks arriving according to a general counting process. Let M₁ and M₂ be the random number of shocks that cause the failure of the first and the second device, respectively. We find conditions on the counting process such that the mean residual life ordering, the increasing convex ordering and the expectation ordering between M₁ and M₂ are preserved in the random lifetimes of the two devices.     

Metaheuristics for the linear ordering problem with cumulative costs

The linear ordering problem with cumulative costs (LOPCC) is a variant of the well-known linear ordering problem, in which a cumulative propagation makes the objective function highly non-linear. The LOPCC has been recently introduced in the context of mobile-phone telecommunications. In this paper we propose two metaheuristic methods for this NP-hard problem. The first one is based on the GRASP methodology, while the second one implements an Iterated Greedy-Strategic Oscillation procedure. We also propose a post-processing based on Path Relinking to obtain improved outcomes. We compare our methods with the state-of-the-art procedures on a set of 218 previously reported instances. The comparison favors the Iterated Greedy - Strategic Oscillation with the Path Relinking post-processing, which is able to identify 87 new best objective function values.     

Large deviations ordering of point processes in some queueing networks

Given a stochastic ordering between point processes, say that a p.p. N is smooth if it is less than the Poisson process with the same average intensity for this ordering. In this article we investigate whether initially smooth processes retain their smoothness as they cross a network of FIFO ·/D/1 queues along fixed routes. For the so-called strong variability ordering we show that point processes remain smooth as they proceed through a tandem of quasi-saturated (i.e., loaded to 1) M+·/D/1 queues. We then introduce the Large Deviations ordering, which involves comparison of the rate functions associated with Large Deviations Principles satisfied by the point processes. For this ordering, we show that smoothness is retained when the processes cross a feed-forward network of unsaturated ·/D/1 queues. We also examine the LD characteristics of a deterministic p.p. at the output of an M+·/D/1 queue. This revised version was published online in June 2006 with corrections to the Cover Date.     

A Solution Concept for Fuzzy Multiobjective Programming Problems Based on Convex Cones

A solution concept for fuzzy multiobjective programming problems based on ordering cones (convex cones) is proposed in this paper. The notions of ordering cones and partial orderings on a vector space are essentially equivalent. Therefore, the optimality notions in a real vector space can be elicited naturally by invoking a concept similar to that of the Pareto-optimal solution in vector optimization problems. We introduce a corresponding multiobjective programming problem and a weighting problem of the original fuzzy multiobjective programming problem using linear functionals so that the optimal solution of its corresponding weighting problem is also the Pareto-optimal solution of the original fuzzy multiobjective programming problem.     

两类供应风险下装配商的最优订购策略

针对两类供应风险(不确定产能与随机产出率)下装配制造商的零部件订购决策这一难题,运用随机非线性规划方法,以装配商期望利润最大化为目标,建立零部件订购决策的多维优化模型,刻画了确定需求下的最优订购量,并对其进行了灵敏性分析。最后,通过数值算例验证了模型结论并进一步探讨不同类供应风险的影响,为装配商的零部件订购决策和风险管理提供有益的管理启示。     

Estimating Stochastically Ordered Survival Functions via Geometric Programming

Many procedures have been proposed to compute nonparametric maximum likelihood estimators (NPMLEs) of survival functions under stochastic ordering constraints. However, each of them is only applicable to a specific type of stochastic ordering constraint and censoring, and is often hard to implement. In this article, we describe a general and flexible method based on geometric programming for computing the NPMLEs from right- or interval-censored data. To this end, we show that the monotonicity properties of the likelihood function and the stochastic ordering constraints considered in the literature allow us to reformulate the estimation problem as a geometric program (GP), a special type of mathematical optimization problem, which can be transformed to a convex optimization problem, and then solved globally and efficiently. We apply this GP-based method to real data examples to illustrate its generality in handling different types of ordering constraints and censoring. We also conduct simulation studies to examine its numerical performance for various sample sizes. Supplemental materials including technical details, computer code, and data files are available online.