基于AGENT的装备供应链仿真模型设计与实现

通过计算机对装备供应链系统进行仿真,可以获得许多宝贵的数据,减少相应的风险,增强决策的科学性,提高战时装备供应保障的科学化、现代化水平。文章构建了基于Agent的装备供应链仿真模型,利用Swarm仿真平台描述了Agent仿真模型,并运用Java语言,实现了Swarm平台下的Agent的交互。     

Three Sides of Smoothing: Categorical Data Smoothing, Nonparametric Regression, and Density Estimation

The past forty years have seen a great deal of research into the construction and properties of nonparametric estimates of smooth functions. This research has focused primarily on two sides of the smoothing problem: nonparametric regression and density estimation. Theoretical results for these two situations are similar, and multivariate density estimation was an early justification for the Nadaraya-Watson kernel regression estimator.
A third, less well-explored, strand of applications of smoothing is to the estimation of probabilities in categorical data. In this paper the position of categorical data smoothing as a bridge between nonparametric regression and density estimation is explored. Nonparametric regression provides a paradigm for the construction of effective categorical smoothing estimates, and use of an appropriate likelihood function yields cell probability estimates with many desirable properties. Such estimates can be used to construct regression estimates when one or more of the categorical variables are viewed as response variables. They also lead naturally to the construction of well-behaved density estimates using local or penalized likelihood estimation, which can then be used in a regression context. Several real data sets are used to illustrate these points.     

Modelling and Estimation for Bivariate Financial Returns

Maximum likelihood estimates are obtained for long data sets of bivariate financial returns using mixing representation of the bivariate (skew) Variance Gamma (VG) and two (skew) t distributions. By analysing simulated and real data, issues such as asymptotic lower tail dependence and competitiveness of the three models are illustrated. A brief review of the properties of the models is included. The present paper is a companion to papers in this journal by Demarta & McNeil and Finlay & Seneta.     

Modelling Category Inflation with Multiple Inflation Processes: Estimation,Specification and Testing1

Zero‐inflated ordered probit (ZIOP) and middle‐inflated ordered probit (MIOP) models are finding increasing favour in the discrete choice literature. We propose generalizations to these models – which collapse to their ZIOP/MIOP counterparts under a set of simple parameter restrictions – with respect to the inflation process. These generalizations form the basis of a new specification test of the inflation process in ZIOP and MIOP models. Support for our generalization framework is principally demonstrated by revisiting a key ZIOP application from the economics literature, and reinforced by the reassessment of an important MIOP application from political science. Our specification test supports the generalized models over the original ZIOP/MIOP ones, suggesting an important role for it in modelling zero‐ and middle‐inflation processes.     

Modelling Category Inflation with Multiple Inflation Processes: Estimation,Specification and Testing1

Zero-inflated ordered probit (ZIOP) and middle-inflated ordered probit (MIOP) models are finding increasing favour in the discrete choice literature. We propose generalizations to these models – which collapse to their ZIOP/MIOP counterparts under a set of simple parameter restrictions – with respect to the inflation process. These generalizations form the basis of a new specification test of the inflation process in ZIOP and MIOP models. Support for our generalization framework is principally demonstrated by revisiting a key ZIOP application from the economics literature, and reinforced by the reassessment of an important MIOP application from political science. Our specification test supports the generalized models over the original ZIOP/MIOP ones, suggesting an important role for it in modelling zero- and middle-inflation processes.     

Stationary-Increment Variance-Gamma and t Models: Simulation and Parameter Estimation

We detail a method of simulating data from long range dependent processes with variance-gamma or t distributed increments, test various estimation procedures [method of moments (MOM), product-density maximum likelihood (PMLE), non-standard minimum χ² and empirical characteristic function estimation] on the data, and assess the performance of each. The investigation is motivated by the apparent poor performance of the MOM technique using real data ( Tjetjep & Seneta, 2006 ); and the need to assess the performance of PMLE for our dependent data models. In the simulations considered the product-density method performs favourably.     

Designs for Variance Components Estimation: Past and Present

This article provides (1) a comprehensive coverage of the literature on designs for estimating variance components, and (2) a review of recent applications of such designs in genetics, statistical process control, and quality improvement. In addition, recent methods of estimation of variance components and model forms, other than the linear, are discussed. The latter developments have a direct effect on the choice of design. Some suggested ideas for future research directions are also given.     

Spatial Growth Regressions: Model Specification,Estimation and Interpretation

Abstract

We attempt to clarify a number of points regarding use of spatial regression models for regional growth analysis. We show that as in the case of non-spatial growth regressions, the effect of initial regional income levels wears off over time. Unlike the non-spatial case, long-run regional income levels depend on: own region as well as neighbouring region characteristics, the spatial connectivity structure of the regions, and the strength of spatial dependence. Given this, the search for regional characteristics that exert important influences on income levels or growth rates should take place using spatial econometric methods that account for spatial dependence as well as own and neighbouring region characteristics, the type of spatial regression model specification, and weight matrix. The framework adopted here illustrates a unified approach for dealing with these issues.     

Supply chain immune system: concept,framework, and applications

Behind every product and service is a supply chain. These supply chains are extremely complex and vulnerable to multifarious risks that threaten their performance and stability, ranging from simple machine or truck breakdowns to catastrophic natural disasters. This paper presents a novel framework for supply chain risk management based on the analogy of the biological immune system, which has multiple layers of increasing sophistication to neutralise a variety of risks. The various layers include: physical barriers, innate response, and adaptive response. The working of the framework is explained with an illustrative semiconductor supply chain. Applications of this framework include short-term disruption response and long-term immunisation, providing planner and manager level insights respectively.     

Labour Values,Prices of Production and the Effects of Income Distribution: Evidence from the Greek Economy

This paper explores the relationship between labour values, prices of production and changes in income distribution in an actual economy. For this purpose we use a linear model of production with circulating capital and homogeneous labour, assuming that wages are paid ex ante. On the basis of this model and data from input–output tables of the Greek economy for the period 1988–1997 we estimate the labour values and prices of production, which are normalized with the use of the Sraffian standard commodity and the actual output vector. Furthermore, we extend Steedman's polynomial approximation of prices of production to include the case where wages are paid ex ante and the accuracy of this approximation is tested with actual input–output data. Finally, we find that prices of production change as a result of hypothetical changes in income distribution more often than not in a monotonic way and in a few cases display curvatures that reverse the order between prices of production and values.     

Estimation of a k-monotone density: characterizations, consistency and minimax lower bounds

The classes of monotone or convex (and necessarily monotone) densities on     can be viewed as special cases of the classes of k - monotone densities on     . These classes bridge the gap between the classes of monotone (1-monotone) and convex decreasing (2-monotone) densities for which asymptotic results are known, and the class of completely monotone (∞-monotone) densities on     . In this paper we consider non-parametric maximum likelihood and least squares estimators of a k -monotone density g ₀. We prove existence of the estimators and give characterizations. We also establish consistency properties, and show that the estimators are splines of degree k −1 with simple knots. We further provide asymptotic minimax risk lower bounds for estimating the derivatives     , at a fixed point x ₀ under the assumption that     .     

供应链的权力、契约、信任网络及其特征——基于社会网络分析

针对近年来供应链不再仅仅局限于企业内部或者某一链条上而是形成了企业间的供应链网络这种现象,基于理论演绎和社会网络分析,对供应链网络及其特征进行了探索性研究。首先基于格里菲提出的市场型、模块型、关系型、受制型、层级型治理结构模型,从社会网络角度对五种供应链治理结构的网络特征做了初步探索,进而构建了五种治理结构的交易网络和社会网络,其中社会网络又分为权力网络、契约网络和信任网络。通过分析发现,市场型治理结构的契约网络比较密集,关系型治理结构的信任网络比较密集,而层级型治理结构的权力网络比较密集。     

Supply chain agility: review,classification and synthesis

Supply chain agility (SCA) has emerged as an important capability to remain competitive in this era of business uncertainty and turbulence. This study aims to gain knowledge of the current state of research on SCA, specifically to have conceptual clarity and synthesise future research avenues. To achieve these goals, we have carried out a systematic review of 118 research papers on SCA published from 1999 to 2016. The findings suggest that the domain has witnessed steady growth since its inception, but little consensus has been observed around its definition and boundaries. To counter these definitional ambiguities, we have presented a comprehensive definition of SCA. The paper further discusses SCA along three thematic categories: the first considers SCA from the strategic perspective, the second considers SCA as a capability and focuses on its enablers and the third explores the impact of SCA on performance. Finally, towards the conclusion, a holistic framework summarising the findings is presented.     

信任、关系承诺与供应链组织耦合:概念性框架

通过文献回顾的方式归纳了信任的类型、关系承诺的要素,并将供应链组织耦合分为作业面和管理面两个维度。通过讨论三者之间的关系,发现信任有助于建立组织间关系承诺,而这两者都有助于提高供应链组织间耦合度,从而提出了三者关系的概念性框架。     

Input–Output Analysis,Labour Scarcity and Relative Price Endogeneity: Aggregate Demand Disturbances in a ‘Flex-price’ Leontief System

In this paper, we introduce scarcity into a conventional demand-driven input–output system to produce a ‘flex-price’ Leontief model. We retain the fixed technical coefficients but allow changes in relative prices to reflect variations in the real wage. Because the consumption coefficients increase with the real wage, the aggregate labour demand curve is found to be upward sloping. This produces conventional results, as long as the labour supply curve is perfectly elastic (horizontal). However, once we introduce labour scarcity, in the form of an upward sloping labour supply function, we derive the seemingly paradoxical result that the output and employment effects of a demand expansion are greater here than in conventional input–output. Through simulation, this result is found to be strongly dependent on the assumption of export exogeneity.     

基于BP神经网络、蒙特卡罗模拟与核估计的经济增长预测研究

构建和训练以投资、消费、政府支出和出口变化率为输入变量,GDP增长率为输出变量的BP神经网络。在假设输入变量服从给定概率分布情况下,采用蒙特卡罗模拟网络输出GDP增长率,并通过核估计估算GDP增长率概率分布曲线。     

产品设计、流程设计与供应链设计决策协调:RBTO研究的新视角

在文献研究与行业调查的基础上,回顾了快速按订单生产（Rapid Build-to-Order,RBTO）模式的实践与研究进展;继而在剖析RBTO局部使能技术和管理策略功效不足的同时,提出产品设计、流程设计与供应链设计决策协调是提升RBTO系统响应性的最根本途径;并从原型行业的成功经验、汽车行业推行RBTO的现实困境以及经典生产模式的运作规律等方面进一步论述了上列观点;最后就新视角下的RBTO研究进行了展望。