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.     

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.     

Assortment optimization with position effects under the nested logit model

We study the assortment optimization problem with position effects under the nested logit model, whose goal is to find the revenue-maximizing subset of products as well as their corresponding display positions. In this joint assortment-position optimization problem, the choices of products are affected by not only their qualities and prices but also the positions where they are displayed. Despite determining the assortment and their corresponding display positions sequentially, we propose to solve this problem in an integrated way to obtain the optimal solution. We formulate this problem as a nonlinear binary integer programming model and develop a dynamic programming based solution approach to obtain the optimal assortment-position assignments. We carry out extensive numerical experiments to evaluate the benefit of our integrated approach. The most important insight we discover is that it is not necessarily better to put the most attractive products in the best position. Moreover, we show that compared to the sequential approaches, our approach can improve revenue by 10.38% on average, which suggests that firms should take into consideration position effects when making assortment decisions. Finally, we discuss results related to two extensions of this problem, that is, the special case when positions are preassigned to nests, and the joint assortment-position-price optimization problem.     

多阶段传感器-武器联合任务管理方法

针对动态环境下的传感器-武器联合任务管理问题展开研究。根据在动态作战过程中出现的有效新目标、有效空闲传感器和武器数量设定阶段门限,以决定进入下一阶段的时机,从而构建多阶段的作战过程。从打击方案质量及系统响应时间的角度出发,分析构建分布式作战体系对系统作战效能的影响,使系统在每个任务管理阶段可以决定响应流程。通过仿真实验验证了所构建的分布式作战体系与设定的阶段门限可以明显提升系统的作战效能。     

Optimizing the allocation of components to kits in small-lot,multiechelon assembly systems

The kitting problem in multiechelon assembly systems is to allocate on-hand stock and anticipated future deliveries to kits so that cost is minimized. This article structures the kitting problem and describes several preprocessing methods that are effective in refining the formulation. The model is resolved using an optimizing approach based on Lagrangian relaxation, which yields a separable problem that decomposes into a subproblem for each job. The resulting subproblems are resolved using a specialized dynamic programming algorithm, and computational efficiency is enhanced by dominance properties devised for that purpose. The Lagrangian problem is resolved effectively using subgradient optimization and a specialized branching method incorporated in the branch-and-bound procedure. Computational experience demonstrates that the specialized approach outperforms the general-purpose optimizer OSL. The new solution approach facilitates time-managed flow control, prescribing kitting decisions that promote cost-effective performance to schedule. © 1994 John Wiley & Sons. Inc.     

基于AHP的弹道导弹中段探测任务分配研究

针对弹道导弹中段探测任务分配的问题,通过分析任务,总结归纳出任务优化分配原则,并确定任务优化分配流程.在此基础上,构建了层次分析模型,利用客观评估数据进行GBR在某项指标上的比较,提高两两比较的客观性和精确性.在利用AHP对不同的来袭区域GBR进行任务分配时,区分了主战雷达与备份雷达,也能够为装备受损接替提供一定的参考...     

车辆导航Kalman滤波衰减因子自适应算法实现

系统介绍了车辆导航系统中卡尔曼滤波器的设计,给出了误差校正的方法.提出了一种衰减记忆卡尔曼滤波中衰减因子的自适应估计方法.并在INS/GPS组合导航系统中进行了计算仿真,结果表明该算法能够较好地估计出衰减因子的大小有效地抑制滤波发散,提高导航精度.     

对办好高等院校研究生课程进修教育的思考

近年来,高校纷纷举办各种形式多样的在职研究生课程进修班,针对这一新生的、过热的教育形式,本文从其定位和目前存在问题等方面进行系统分析,并提出了进一步办好研究生课程进修班的措施.     

正确认识和走出CAI的误区

CAI能解决很多传统课堂教学中没有解决的问题,但应该正确认识和使用CAI,CAI是手段而不是目的,应该防止走入CAI的误区。     

谈震后灾区群众的情感情绪疏导

灾区群众的情感、情绪对灾后重建具有重要意义,是灾后重建的一项重要工程。心理帮扶人员要怀着对灾区群众的同情、理解,耐心地进行心理疏导,帮助他们树立重建家园的勇气和信心。