需求信息泄露条件下供应链零售商订货策略研究

针对供应链订货过程中的需求信息泄露现象,通过对比供应商在泄露信息和不泄露信息情况下的收益,研究了供应链需求信息泄露的产生机理。建立了需求信息泄露条件下订货过程中零售商之间的信号博弈模型,通过模型求解得到了分离均衡和混同均衡的存在条件,并对不同均衡状态下零售商的最优订货策略和最优收益进行了分析。在此基础上,进一步讨论了零售商的订货策略选择问题。最后,通过一个数值算例说明了有关结论的有效性。     

Robustness in complex information systems: The role of information “barriers” in Boolean networks

In this supposed “information age,” a high premium is put on the widespread availability of information. Access to as much information as possible is often cited as key to the making of effective decisions. While it would be foolish to deny the central role that information and its flow has in effective decision‐making processes, this chapter explores the equally important role of “barriers” to information flows in the robustness of complex systems. The analysis demonstrates that (for simple Boolean networks at least) a complex system's ability to filter out, i.e., block, certain information flows is essential if it is not to be beholden to every external signal. The reduction of information is as important as the availability of information. © 2009 Wiley Periodicals, Inc. Complexity, 2010     

关于最大熵与信息熵之差的上界讨论

基于自信息函数为一可微凸函数这一事实,利用自信息函数所对应的Jenson离散型不等式,得到了有关最大熵与信息熵之差上界的一些结果.     

任意随机多元函数序列的一类强偏差定理

本文通过概率空间上的任意测度与另一任意测度相比较,研究了任意随机多元函数序列普遍成立的一类强偏差定理.利用网微分法与分析运算法,获得了若干任意信源的Shannon-Mcmillan随机逼近定理,并将已有的关于随机多地函数序列及离散信源的结果加以推广.     

A new structured quasi-Newton algorithm using partial information on Hessian

This paper presents a modified quasi-Newton method for structured unconstrained optimization. The usual SQN equation employs only the gradients, but ignores the available function value information. Several researchers paid attention to other secant conditions to get a better approximation of the Hessian matrix of the objective function. Recently Yabe et al. (2007) [6] proposed the modified secant condition which uses both gradient and function value information in order to get a higher-order accuracy in approximating the second curvature of the objective function. In this paper, we derive a new progressive modified SQN equation, with a vector parameter which use both available gradient and function value information, that maintains most properties of the usual and modified structured quasi-Newton methods. Furthermore, local and superlinear convergence of the algorithm is obtained under some reasonable conditions.     

Optimum calibration points estimating distribution functions

The calibration method has been widely discussed in the recent literature on survey sampling, and calibration estimators are routinely computed by many survey organizations. The calibration technique was introduced in [12] to estimate linear parameters as mean or total. Recently, some authors have applied the calibration technique to estimate the finite distribution function and the quantiles. The computationally simpler method in [14] is built by means of constraints that require the use of a fixed value t₀. The precision of the resulting calibration estimator changes with the selected point t₀. In the present paper, we study the problem of determining the optimal value t₀ that gives the best estimation under simple random sampling without replacement. A limited simulation study shows that the improvement of this optimal calibrated estimator over possible alternatives can be substantial.     

An adjustment scheme for nonlinear pricing problem with two buyers

We examine a contracting problem with asymmetric information in a monopoly pricing setting. Traditionally, the problem is modeled as a one-period Bayesian game, where the incomplete information about the buyers’ preferences is handled with some subjective probability distribution. Here we suggest an iterative online method to solve the problem. We show that, when the buyers behave myopically, the seller can learn the optimal tariff by selling the product repeatedly. In a practical modification of the method, the seller offers linear tariffs and adjusts them until optimality is reached. The adjustment can be seen as gradient adjustment, and it can be done with limited information and so that it benefits both the seller and the buyers. Our method uses special features of the problem and it is easily implementable.     

Set choice problems with incomplete information about the preferences of the decision maker

We consider the problem of selecting a predetermined number of objects from a given finite set. It is assumed that the preferences of the decision maker on this set are only partially known. Our solution approach is based on the notions of optimal and non-dominated subsets. The properties of such subsets and the objects they contain are investigated. The implementation of the developed approach is discussed and illustrated by various examples.     

带ARMA有色噪声的广义系统信息融合Kalman平滑器

对于带自回归滑动平均(ARMA)有色观测噪声的多传感器广义离散随机线性系统,应用奇异值分解,提出了广义系统多传感器信息融合状态平滑问题。基于Kalman滤波方法,在线性最小方差信息融合准则下,给出了按矩阵加权融合降阶稳态广义Kalman平滑器。为了计算最优加权,提出了局部平滑误差协方差阵的计算公式。一个Monte Carlo仿真例子说明了所提方法的有效性。     

电子商务信息系统安全管理体系PRS-ISMS的研究

信息是电子商务至关重要的资产,电子商务的正常运转必须建立在安全的信息系统之上,因而电子商务信息系统安全问题成为人们日益关注的重点.根据电子商务信息系统特点,从信息系统过程(Process)、资源(Resource)和安全目标(Security)三个视角分析了电子商务信息安全风险的要素及其关系,构建了三维信息系统安全管理体系模型PRS-ISMS,提出了改进的信息安全风险管理过程PRS-PDCA.