Flow shop scheduling with deteriorating jobs under dominating machines

This paper addresses no-wait or no-idle flow shop scheduling problems with deteriorating jobs, i.e., jobs whose processing times are an increasing function of their starting time. A simple linear deterioration function is assumed and some dominating relationships between machines can be satisfied. It is shown that for the problems to minimize makespan or weighted sum of completion time, polynomial algorithms still exist, although these problems are more complicated than the classical ones. When the objective is to minimize maximum lateness or maximum tardiness, the solutions of a classical version may not hold.     

异质产品供应链定价控制权与零售商横向兼并效应分析

针对一部线性合约与供应商是否具有绝对定价控制权,比较分析零售商横向兼并集中度提高对消费者福利的影响.结果表明,(1)当供应商具有绝对定价控制权时,零售商横向兼并对消费者产生的影响取决于产品替代性程度大小:若替代性程度较高,则将产生有利影响,反之,将产生不利影响;(2)当供应商没有绝对定价控制权时,零售商横向兼并对消费者产生的影响取决于零售商兼并前的相对定价控制权强弱与兼并后的相对定价控制权增幅大小:若零售商在供应链中处于相对弱势地位,且零售商横向兼并使零售商的定价控制权增幅较大,则兼并将对消费者产生有利影响,否则,将对消费者产生不利影响.     

Pipage Rounding: A New Method of Constructing Algorithms with Proven Performance Guarantee

The paper presents a general method of designing constant-factor approximation algorithms for some discrete optimization problems with assignment-type constraints. The core of the method is a simple deterministic procedure of rounding of linear relaxations (referred to as pipage rounding). With the help of the method we design approximation algorithms with better performance guarantees for some well-known problems including MAXIMUM COVERAGE, MAX CUT with given sizes of parts and some of their generalizations.     

学校本位教学视导模式的实证研究——以兰州市E中学为例

本研究目的在于通过对兰州市E中学施行的学校本位教学视导模式的深入观察,全方位了解学校本位教学视导模式的具体运作方式。以兰州市一所薄弱学校为研究场域,通过课堂观察的方式,全面了解学校为提高办学质量所开展的“学案分组教学法”,及进行学校本位化视导模式的具体运作状态。在兰州市E中学开展学校本位教学视导模式的过程中,学校校长与某大学教育学院课程与教学领域的教授专家参与视导过程。主要采取校长主导,专家参与的合作视导方式,对兰州市E中学初中二年级屈老师数学课进行为期一周的教学观察与记录。实施以学校为本位的合作视导方式,目的在于发现兰州市E中学进行“学案分组教学法”中的具体教学问题,通过大学与中学的合作,开展学校本位视导模式,有效促进教师的专业发展与增强教学有效性,提高学校办学质量。     

Estimation for Partially Linear Single-index Instrumental Variables Models

In this article, we generalize the partially linear single-index models to the scenario with some endogenous covariates variables. It is well known that the estimators based on the existing methods are often inconsistent because of the endogeneity of covariates. To deal with the endogenous variables, we introduce some auxiliary instrumental variables. A three-stage estimation procedure is proposed for partially linear single-index instrumental variables models. The first stage is to obtain a linear projection of endogenous variables on a set of instrumental variables, the second stage is to estimate the link function by using local linear smoother for given constant parameters, and the last stage is to obtain the estimators of constant parameters based on the estimating equation. Asymptotic normality is established for the proposed estimators. Some simulation studies are undertaken to assess the finite sample performance of the proposed estimation procedure.     

Transient detailed balance and product form for reaction networks

This paper explores the boundary of the set of reaction networks that have an exact transient (truncated) multidimensional Poisson or product-form distribution for the number of particles of different types. Motivated by the birth–death process, we introduce the notions of transient detailed balance and delay functions, and use these notions to obtain the novel transient product-form distribution in a coagulation-fragmentation process for polymers with a tree-like structure from that of the pure coagulation process.     

Marginal likelihood estimation from the Metropolis output: tips and tricks for efficient implementation in generalized linear latent variable models

The marginal likelihood can be notoriously difficult to compute, and particularly so in high-dimensional problems. Chib and Jeliazkov employed the local reversibility of the Metropolis–Hastings algorithm to construct an estimator in models where full conditional densities are not available analytically. The estimator is free of distributional assumptions and is directly linked to the simulation algorithm. However, it generally requires a sequence of reduced Markov chain Monte Carlo runs which makes the method computationally demanding especially in cases when the parameter space is large. In this article, we study the implementation of this estimator on latent variable models which embed independence of the responses to the observables given the latent variables (conditional or local independence). This property is employed in the construction of a multi-block Metropolis-within-Gibbs algorithm that allows to compute the estimator in a single run, regardless of the dimensionality of the parameter space. The counterpart one-block algorithm is also considered here, by pointing out the difference between the two approaches. The paper closes with the illustration of the estimator in simulated and real-life data sets.     

Bandwidth selection through cross-validation for semi-parametric varying-coefficient partially linear models

We study bandwidth selection for a class of semi-parametric models. The proper choice of optimal bandwidth minimizes the prediction errors of the model. We provide detailed derivation of our procedure and the corresponding computation algorithms. Our proposed method simplifies the computation of the cross-validation criteria and facilitates more complicated inference and analysis in practice. A data set from Wisconsin Diabetes Registry has been analysed as an illustration.     

Results concerning the generalized partially linear single-index model

The central topic of this article is the estimation of parameters of the generalized partially linear single-index model (GPLSIM). Two numerical optimization procedures are presented and an S-plus program based on these procedures is compared to a program by Wand in a simulation setting. The results from these simulations indicate that the estimates for the new procedures are as good, if not better, than Wand's. Also, this program is much more flexible than Wand's since it can handle more general models. Other simulations are also conducted. The first compares the effects of using linear interpolation versus spline interpolation in an optimization procedure. The results indicate that by using spline interpolation one gets more stable estimates at a cost of increased computational time. A second simulation was conducted to assess the performance of a method for estimating the variance of alpha. A third set of simulations is carried out to determine the best criterion for testing that one of the elements of alpha is equal to zero. The GPLSIM is applied to a water quality data set and the results indicate an interesting relationship between gastrointestinal illness and turbidity (cloudiness) of drinking water.     

On partial linear additive isotonic regression

In this paper we discuss semiparametric additive isotonic regression models. We discuss the efficiency bound of the model and the least squares estimator under this model. We show that the ordinary least square estimator studied by Huang (2002) and Cheng (2009) for the semiparametric isotonic regression achieves the efficiency bound for the regular estimator when the true parameter belongs to the interior of the parameter space. We also show that the result by Cheng (2009) can be generalized to the case that the covariates are dependent on each other.