基于成员合作的组织有效性建模分析

从组织成员合作出发,通过建立博弈模型研究成员目标优化问题,建立线性规划模型研究组织目标优化问题,并把个人目标优化条件下成员投入的人力资源作为组织目标优化的资源约束,以此建立博弈分析和线性规划的联系,使个人目标优化和组织目标优化结合起来,并在此基础上形成基于成员合作的组织有效性分析模型。     

基于网络资源利用的“程序设计”课程模式研究

文章探讨了基于网络资源利用的程序设计课程教学模式,从教学目标、教学策略、教学评价等方面展开研究,并分析实践效果,认为该教学模式有利于培养信息时代高素质人才。     

区域微电子技术发展实力综合评价研究

本文运用模糊数学方法,建立了多层次模糊综合评判模型。并根据实际情况选用不同算子,对中国区域微电子技术发展实力进行了综合评价,为有关部门制订微电子技术区域发展政策提供了参考。     

新疆制造业品牌运营的问题及对策

针对近年来新疆制造业在品牌运营中存在的品牌数量少、品牌缺乏个性等问题,在其相应成因分析的基础上,认为做好品牌设计、搞好品牌定位、品牌推广和维护是新疆制造业品牌运营的必然选择。从政府和企业的角度提出了新疆制造业进行品牌运营的思路与对策。     

New balanced sampling plans excluding adjacent units

Hedayat et al. [1988a. Sampling plans excluding contiguous units. J. Statist. Plann. Inference 19, 159–170; 1988b. Designs in survey sampling avoiding contiguous units. In: Krishnaiah, P.R., Rao, C.R. (Eds.). Handbook of Statistics, vol. 6. Elsevier, Amsterdam, pp. 575–583] first introduced balanced sampling designs for the exclusion of contiguous units. Sampling plans that excluded the selection of contiguous units within a given sample, while maintaining a constant second-order inclusion probability for non-contiguous units, were investigated for finite populations of N units arranged in a circular, one-dimensional ordering. There remain many open questions about the existence of such plans and their extension to plans excluding adjacent units. We present new generation techniques and new balanced sampling plans for the exclusion of adjacent units under finite, one-dimensional, circularly and linearly ordered populations.     

Dynamic Pricing to Minimize Maximum Regret

We consider a dynamic pricing problem that involves selling a given inventory of a single product over a short, two‐period selling season. There is insufficient time to replenish inventory during this season, hence sales are made entirely from inventory. The demand for the product is a stochastic, nonincreasing function of price. We assume interval uncertainty for demand, that is, knowledge of upper and lower bounds but not a probability distribution, with no correlation between the two periods. We minimize the maximum total regret over the two periods that results from the pricing decisions. We consider a dynamic model where the decision maker chooses the price for each period contingent on the remaining inventory at the beginning of the period, and a static model where the decision maker chooses the prices for both periods at the beginning of the first period. Both models can be solved by a polynomial time algorithm that solves systems of linear inequalities. Our computational study demonstrates that the prices generated by both our models are insensitive to errors in estimating the demand intervals. Our dynamic model outperforms our static model and two classical approaches that do not use demand probability distributions, when evaluated by maximum regret, average relative regret, variability, and risk measures. Further, our dynamic model generates a total expected revenue which closely approximates that of a maximum expected revenue approach which requires demand probability distributions.     

中华女子学院教工运动会管理系统的设计与应用

中华女子学院教工运动会管理系统采用Visual Basic＋Access的体系结构，具有友好的操作界面，使用方便，能够完成从赛前报名、比赛编组、成绩统计、得分计算到成绩报告单的打印输出等运动会的各项信息管理和组织功能，大大提高了工作效率，并在实际应用中发挥了良好作用。     

On Integer Programming Approaches for Morphological Template Decomposition Problems in Computer Vision

In morphological image processing and analysis, a template or structuringelement is applied to an image. Often savings in computation time and abetter fit to the given computer architecture can be achieved by using thetechnique of template decomposition. Researchers have written a multitude ofpapers on finding such decompositions for special classes of templates.Justifying recent integer programming approaches to the morphologicaltemplate decomposition problem in its general form, this paper proves theNP-completeness of this problem.     

非线性混合整数规划的罚函数解法

主要对非线性混合整规划问题的求解进行探讨。利用罚函数把非线性混合整规划问题转化为等价的非线性规划问题,从而可通过求解一个无约束线性规划问题而得到原问题的最优解。     

Joint Initial Stocking and Transshipment—Asymptotics and Bounds

A common problem faced by many firms in their supply chains can be abstracted as follows. Periodically, or at the beginning of some selling season, the firm needs to distribute finished goods to a set of stocking locations, which, in turn, supply customer demands. Over the selling season, if and when there is a supply‐demand mismatch somewhere, a re‐distribution or transshipment will be needed. Hence, there are two decisions involved: the one‐time stocking decision at the beginning of the season and the supply/transshipment decision throughout the season. Applying a stochastic dynamic programming formulation to a two‐location model with compound Poisson demand processes, we identify the optimal supply/transshipment policy and show that the optimal initial stocking quantities can be obtained via maximizing a concave function whereas the contribution of transshipment is of order square‐root‐of T. Hence, in the context of high‐volume, fast‐moving products, the initial stocking quantity decision is a much more important contributor to the overall profit. The bounds also lead to a heuristic policy, which exhibits excellent performance in our numerical study; and we further prove both the bounds and the heuristic policy are asymptotically optimal when T approaches infinity. Extension to multiple locations is also discussed.