Distribution lot-sizing models for arborescent supply chains with discrete-period variable demand

This study formulates a novel mixed-integer programming lot-sizing model for arborescent supply chains with discrete-period variable demand and then develops an efficient two-phase heuristic method, in which a combined multi-period demand ordering policy, rather than the lot-for-lot ordering policy usually assumed in previous papers, is adopted. Two important properties are introduced and used to obtain a better initial feasible solution. The good performance of the proposed heuristic method is verified through a comparison with the optimal solution method. It is also shown that the performance of the proposed combined multi-period demand ordering method is superior to that of the lot-for-lot ordering method. Sensitivity analysis is conducted to explore the impacts of changing the values of relevant parameters on the total supply chain cost, the total number of orders and the total number of opened members. Finally, a well-known logistics company in Taiwan is chosen to demonstrate the excellent performance and the aptness of the proposed ordering method.     

杂合灰色聚类与变精度粗糙模糊集的概率决策方法及应用

在基于粗糙集理论或扩展粗糙集理论的不确定性决策中,仅由数据集无法获得决策表,同时由于决策属性呈现模糊性,以致于难以获取概率决策规则。针对这一类决策问题,基于灰色定权聚类与优势粗糙集变精度方法,本文构建了一种的杂合决策方法。该方法首先利用中心点三角白化权函数的灰色定权聚类方法将包含不同量纲指标的知识表示系统生成多属性决策表,而后运用变精度粗糙模糊集进行决策分析,生成概率决策规则,最后以区域关键技术的选择为例,表明该模型的可行性与实用性。     

Universal equation for the relative change in profit of manufacturing company

In contemporary conditions of the company's business operations, where high dynamics of costs, sales volume and change of production programme is present, it is of crucial importance to investigate their effects on the change of profit. Starting from cost–volume–profit equation, the aim is to arrive at a universal equation that will simultaneously measure a relative change in profit for a number of products, not only under the influence of change in sales volume but also of other relevant variables, such as sales price, fixed and variable costs. The basic hypothesis is that it is possible to establish in a form of universal equation the dependence between the change in profit and change in influential variables. In this investigation, first it was observed the partial influence of some variables on the change in profit and their dependence was determined for a single product, and then for more than one product. Finally, by summing up all those effects, a universal equation of profit change was obtained. The derived universal equation for the relative change in profit along with simultaneous effects of several variables makes possible for the company management to more simply determine the profit for diverse conditions of business operations. The universal equation for the relative change in profit was applied in one company and the results obtained confirm its significance.     

基于零膨胀分位数两部模型的银行贷款违约预测研究

贷款信用风险评估是银行风控的重要内容。贷款逾期天数作为常见的风险度量指标,具有典型的零膨胀特征。对于零膨胀数据,传统的线性回归不再适用,两部模型是常用的代表方法。考虑到贷款数据具有偏态分布特征,本文构建了一个分位数两部模型—logit-quantile模型。该模型由Logistic回归和分位数回归构成,为了进行风险因素的选择,在模型的两个回归中添加了Lasso惩罚。为了求解模型,本文采用了坐标下降法和线性规划法相结合的迭代算法。模拟分析显示,对比逐步法和常用的logit-linear两部模型,新模型表现出了最好的变量选择效果,尤其在零膨胀比例为80%及高维情形时,该模型的表现仍然最优。最后对某银行的贷款数据实证分析显示,新模型具有更精简的结构,采用交叉验证技术进行预测显示新模型的预测和分类表现最好。     

十年来中国抗争运动研究评述

上世纪90年代以来,中国的抗争运动爆发的频度和影响力不断增长,吸引了越来越多研究者的关注,海内外关于这一题域的研究也日渐兴起。这一研究题域在概念谱系上呈现出多元化的状态,以过程分析、结构分析和机制分析作为其主要的分析路径,以集体行动、日常抵抗、社会动员以及政治过程等理论为指导,并特别关注抗争运动与民主政治的关系;在研究方法上,规范性实证研究的比例正在上升,定量研究和比较研究是未来的发展方向。     

Projection‐Based Statistical Inference in Linear Structural Models with Possibly Weak Instruments

It is well known that standard asymptotic theory is not applicable or is very unreliable in models with identification problems or weak instruments. One possible way out consists of using a variant of the Anderson–Rubin ((1949), AR) procedure. The latter allows one to build exact tests and confidence sets only for the full vector of the coefficients of the endogenous explanatory variables in a structural equation, but not for individual coefficients. This problem may in principle be overcome by using projection methods (Dufour (1997), Dufour and Jasiak (2001)). At first sight, however, this technique requires the application of costly numerical algorithms. In this paper, we give a general necessary and sufficient condition that allows one to check whether an AR‐type confidence set is bounded. Furthermore, we provide an analytic solution to the problem of building projection‐based confidence sets from AR‐type confidence sets. The latter involves the geometric properties of “quadrics” and can be viewed as an extension of usual confidence intervals and ellipsoids. Only least squares techniques are needed to build the confidence intervals.     

Generalized inferences on the common mean vector of several multivariate normal populations

The hypothesis testing and confidence region are considered for the common mean vector of several multivariate normal populations when the covariance matrices are unknown and possibly unequal. A generalized confidence region is derived using the concepts of generalized method based on the generalized p$p$-value. The generalized confidence region is illustrated with two numerical examples. The merits of the proposed method are numerically compared with those of existing methods with respect to their expected area or expected d-dimensional volumes and coverage probabilities under different scenarios.     

Multistage sampling for latent variable models

I consider the design of multistage sampling schemes for epidemiologic studies involving latent variable models, with surrogate measurements of the latent variables on a subset of subjects. Such models arise in various situations: when detailed exposure measurements are combined with variables that can be used to assign exposures to unmeasured subjects; when biomarkers are obtained to assess an unobserved pathophysiologic process; or when additional information is to be obtained on confounding or modifying variables. In such situations, it may be possible to stratify the subsample on data available for all subjects in the main study, such as outcomes, exposure predictors, or geographic locations. Three circumstances where analytic calculations of the optimal design are possible are considered: (i) when all variables are binary; (ii) when all are normally distributed; and (iii) when the latent variable and its measurement are normally distributed, but the outcome is binary. In each of these cases, it is often possible to considerably improve the cost efficiency of the design by appropriate selection of the sampling fractions. More complex situations arise when the data are spatially distributed: the spatial correlation can be exploited to improve exposure assignment for unmeasured locations using available measurements on neighboring locations; some approaches for informative selection of the measurement sample using location and/or exposure predictor data are considered.     

微分方程的解关于部分变元的弱吸引性

本文提出关于部分变元的弱吸引及其相关概念,并给出判定他们的充分条件。文献[]、[]中的相应结果可作为本文的特例。12     

集成电路中布尔线路图的优化设计

二叉决策图（BDDs)是布尔函数的一个表示方法,最近它被广泛应用于逻辑综合中布尔电路的模拟和测试等领域。在这些应用中,有些基本问题需要解决,其中包括电路图到决策图的转换。文章提出了一个转换的方法并分两步叙述,首先是对无扇出电路的转换,然后是对有扇出电路的转换,最后把两者结合为一个通用算法。