轴对称静电场不等距多重网格法的研究

研究了不等距多重网格法,可用于区域形状任意和有内电极的实际电子光学系统轴对称电场的计算,特别是对于求解区域大、部分区域电场精度要求高的场合,较好地解决了计算精度与划分网格点数之间的矛盾,可广泛应用于分析设计静电聚焦像管的电子光学系统,以及摄像管电子枪的发射系统等.     

分布式虚拟环境中环境信息动态更新研究

环境信息动态更新是分布式虚拟环境的一个主要特点,如何使环境信息更新更活跃、更反应实际情况,一直是分布式虚拟环境研究的重点。在典型的分布式交互环境中,环境信息动态更新是基于协议数据单元(PDU),它不提供数据可靠性传输保证。如何保证分布式环境中各结点环境信息一致性,本文提出了一种信息校验和协议,它通过极少的信息传输就可保证各结点环境信息高度一致。文中定义了保证分布式环境信息动态一致性更新的协议数据单元,并在试验环境中证明了协议的可靠性。     

三维静磁场Lipschitz区域上Robin问题广义解的存在与唯一性

近年来,电磁场边值问题的数值解法取得了飞速的发展．由于电磁场边值问题是一类非线性偏微分方程,研究解的存在性、唯一性具有较大的困难．前人已讨论了B-H间的几个基本不等式,并由之证明了三雏静磁场带零边值问题广义解的存在与唯一性,作者也曾利用给出的B-H间的不等式证明了三维静磁场Neumann问题和二维时变场第一边值初值问题广义解的存在与唯一性．由于在一般区域讨论存在困难,作者利用Sobolev空间理论及单调算子理论证明了三雏静磁场Lipschitz区域上Robin问题广义解的存在与唯一性．     

The impact of exponential smoothing forecasts on the bullwhip effect

An important phenomenon often observed in supply chain management, known as the bullwhip effect, implies that demand variability increases as one moves up the supply chain, i.e., as one moves away from customer demand. In this paper we quantify this effect for simple, two‐stage, supply chains consisting of a single retailer and a single manufacturer. We demonstrate that the use of an exponential smoothing forecast by the retailer can cause the bullwhip effect and contrast these results with the increase in variability due to the use of a moving average forecast. We consider two types of demand processes, a correlated demand process and a demand process with a linear trend. We then discuss several important managerial insights that can be drawn from this research. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 269–286, 2000     

浅析失火罪与消防责任事故罪

本文通过介绍《重庆市办理失火罪和消防责任事故罪案件立案标准（暂行）》,简述了失火罪与消防责任事故罪的具体概念、主要构成特征及区别。     

备件保障效能动态评估方法

针对目前效能评估方法多重视效能指标的静态观测值,对时序状态数据所蕴含的趋势信息关注较少的缺点,提出基于灰色聚类-粗糙集和集对分析的备件保障效能动态评估方法。针对主客观赋权方法各自的优缺点,引入依赖度和重要度的概念,建立灰色聚类-粗糙集组合赋权模型;将指标权重引入集对理论,提出集对同势、均势和反势的定义,描述备件保障效能的变化规律,构建基于马尔可夫链的集对分析动态模型。实例分析结果表明,该方法可以有效反映备件保障效能的动态变化特征,为决策者制定备件保障长期计划提供科学依据。     

A worst‐case formulation for constrained ranking and selection with input uncertainty

In this research, we consider robust simulation optimization with stochastic constraints. In particular, we focus on the ranking and selection problem in which the computing time is sufficient to evaluate all the designs (solutions) under consideration. Given a fixed simulation budget, we aim at maximizing the probability of correct selection (PCS) for the best feasible design, where the objective and constraint measures are assessed by their worst‐case performances. To simplify the complexity of PCS, we develop an approximated probability measure and derive the asymptotic optimality condition (optimality condition as the simulation budget goes to infinity) of the resulting problem. A sequential selection procedure is then designed within the optimal computing budget allocation framework. The high efficiency of the proposed procedure is tested via a number of numerical examples. In addition, we provide some useful insights into the efficiency of a budget allocation procedure.     

Social benefits of government investment in enterprises

A critical issue for many governments is boosting the adoption rates of products or technologies that enhance consumer surplus or total social welfare. Governments may, for example, pay subsidies to producers or to consumers to stimulate the manufacture or consumption of specific products, for example, energy-efficient appliances or more effective drugs. This research proposes a strategic government investment policy, namely, share acquisition, and demonstrates its effectiveness in reaching societal objectives. We consider a Cournot quantities-choice market comprised of homogeneous firms where the government intervenes to buy shares, and turning private firms into state-owned enterprises. We recognize that purchasing a single private firm is the optimal policy for the government to reach its societal objectives. Additionally, taking into consideration financial constraints, we find that the optimal stake increases with the budget. Compared with the optimal output-based subsidy policy, when the budget is low, the optimal government investment policy induces a higher consumer surplus. In addition, in differentiated Cournot competition, under which firms compete in selling substitutable products, we find that when the budget is sufficient, the optimal stake purchased first decreases and then increases according to the substitutability level among products.     

Purchase and retrieval competition for seasonal produce

We study the competition problem of purchase and multiretrieval of perishable seasonal produce, where wholesalers purchase and stock their products in the first period, and then retrieve and sell them in subsequent periods. We first consider the duopoly case and assume that the prices are exogenous and fluctuate. In each period, after the price realization, the wholesalers retrieve some stock from their warehouses to satisfy their demands. One wholesaler's unsatisfied customers can switch to another and be satisfied by its left retrieved products. Any unsold retrieved stock has no salvage value and any unsatisfied demand is lost. The unretrieved stock is carried to the next period at a perishable rate. The wholesalers compete for the substitute demand by determining their own purchase and retrieval quantities. We show the existence and uniqueness of a pure-strategy Nash equilibrium, and that the Nash equilibrium strategy has the simple “sell-down-to” structure. We also consider the general N-person game and show the existence of the Nash equilibrium, and characterize the structure of the equilibrium strategy for the symmetric case. In addition, we consider the case with endogenous prices, and show that the problem reduces to a repeated newsvendor game with price and inventory competition. We derive the conditions under which a unique Nash equilibrium exists and characterize the equilibrium strategy. Finally, we conduct numerical studies to examine the impacts of the model parameters on the equilibrium outcomes and to generate managerial insights.     

Synchronizing pricing and replenishment to serve forward-looking customers

We incorporate strategic customer waiting behavior in the classical economic order quantity (EOQ) setting. The seller determines not only the timing and quantities of the inventory replenishment, but also the selling prices over time. While similar ideas of market segmentation and intertemporal price discrimination can be carried over from the travel industries to other industries, inventory replenishment considerations common to retail outlets and supermarkets introduce additional features to the optimal pricing scheme. Specifically, our study provides concrete managerial recommendations that are against the conventional wisdom on “everyday low price” (EDLP) versus “high-low pricing” (Hi-Lo). We show that in the presence of inventory costs and strategic customers, Hi-Lo instead of EDLP is optimal when customers have homogeneous valuations. This result suggests that because of strategic customer behavior, the seller obtains a new source of flexibility—the ability to induce customers to wait—which always leads to a strictly positive increase of the seller's profit. Moreover, the optimal inventory policy may feature a dry period with zero inventory, but this period does not necessarily result in a loss of sales as customers strategically wait for the upcoming promotion. Furthermore, we derive the solution approach for the optimal policy under heterogeneous customer valuation setting. Under the optimal policy, the replenishments and price promotions are synchronized, and the seller adopts high selling prices when the inventory level is low and plans a discontinuous price discount at the replenishment point when inventory is the highest.