Chemists and Biochemists during the National Socialist Era

Chemistry and biochemistry in Germany was notably affected by the dismissal and emigration of Jewish scientists. The expulsion of Jewish scientists aided to significantly reduce the international regard for German science, particularly in biochemistry, physical chemistry, and quantum chemistry, after 1945. In most cases remaining scientists adjusted quickly after 1933 to the new political circumstances, with a few exceptions. A number of them even actively supported the politics of National Socialism. This fact as well as the common stance to forget the 12 years of National Socialist rule complicated the exchange of international scientific knowledge after 1945 and delayed affiliation of the weakened fields of research to the level of international research.     

部分延迟订购的易变质品联合定价与生产策略

构建了一个需求同时依赖于销售价格和库存水平,生产率和变质率均为常数,允许缺货且缺货量部分延迟订购的易变质品联合定价与生产控制模型。首先证明了在销售价格给定的情况下,系统的总利润函数是关于生产计划的严格凹函数,平均利润函数是严格的伪凹函数,即存在唯一的最优解,并给出其充分条件。接着给出问题的一个数值求解算法。最后通过算例,展示了模型及相关算法的应用,并对相关参数进行了灵敏度分析,结果显示:当产品的生产成本、缺货成本和机会成本增加时,系统的平均利润将下降;生产成本和延迟订购阻力系数对最优定价和生产策略以及平均利润的影响较大。     

基于CGE模型的我国西北地区民族经济政策模拟和实证研究

民族经济政策的模拟评估方法的缺失一直以来是我国民族经济政策效果有效性验证的一个短板。本文构建了基于CGE的西北地区民族经济政策评估模型,针对一般转移性支付政策进行系统模拟、政策力度对西北地区的经济要素以及当地企业产出的影响程度纵向对比分析,以及与东部沿海地区横向对比分析。本文的政策评估建模和模拟分析可以为我国西部大开发战略中一般性转移支付政策提供相应的决策支持。     

新产品定价决策的影响因素分析

新产品的成功销售取决于两个重要的因素:一是具有生产特性的工程变量,比如产品的可靠性水平;一是具有市场特征的影响因素,比如价格和保障机制。为了实现收益,制造商必须认真审视价格、产品可靠性和保障机制的选择。因此,本文将价格作为外生变量,将保障机制与可靠性作为决策变量,建立了以最大化为目标的收益模型,分析可靠性与保障机制的最优策略。另外,探讨当不同变量的敏感性参数发生变化时,最优保障机制与产品可靠性的变化规律。最后,通过算例分析收益函数的基本特性,结论显示消费者总是从产品保障机制的信号中判断产品的可靠性水平,这对新产品销售有一定的借鉴意义。     

The randomized threshold for the discrete-time Geo/G/1 queue

This paper discusses a discrete-time Geo/G/1 queue, in which the server operates a random threshold policy, namely 〈p, N〉 policy, at the end of each service period. After all the messages are served in the queue exhaustively, the server is immediately deactivated until N messages are accumulated in the queue. If the number of messages in the queue is accumulated to N, the server is activated for services with probability p and deactivated with probability (1 − p). Using the generating functions technique, the system state evolution is analyzed. The generating functions of the system size distributions in various states are obtained. Some system characteristics of interest are derived. The long-run average cost function per unit time is analytically developed to determine the joint optimal values of p and N at a minimum cost.     

An analytical study of the modification ability of distribution centers

This paper considers a two-level vendor managed inventory (VMI) system comprising a distribution center (DC) and a retailer. Both the DC’s and the retailer’s replenishment decisions follow the order-up-to-level policy and aim at maximizing the profit of the overall system. We critically examine the potential of the DC’s ability to modify delivery decisions, identify and quantify the cost factors that influence the DC’s modification ability, establish a relationship between the DC’s location and its modification ability, and show the trade-off between the DC’s modification ability and related costs. Our analysis provides a new insight into the role of the DC and reveals the full potential of the VMI system. Our findings and their practical implications, demonstrated with the aid of computational examples, are helpful for enhancing the practice of VMI at both strategic and operational levels.     

Optimal policy for a dynamic,non-stationary,stochastic inventory problem with capacity commitment

This paper studies a single-product, dynamic, non-stationary, stochastic inventory problem with capacity commitment, in which a buyer purchases a fixed capacity from a supplier at the beginning of a planning horizon and the buyer’s total cumulative order quantity over the planning horizon is constrained with the capacity. The objective of the buyer is to choose the capacity at the beginning of the planning horizon and the order quantity in each period to minimize the expected total cost over the planning horizon. We characterize the structure of the minimum sum of the expected ordering, storage and shortage costs in a period and thereafter and the optimal ordering policy for a given capacity. Based on the structure, we identify conditions under which a myopic ordering policy is optimal and derive an equation for the optimal capacity commitment. We then use the optimal capacity and the myopic ordering policy to evaluate the effect of the various parameters on the minimum expected total cost over the planning horizon.     

Optimal risk probability for first passage models in semi-Markov decision processes

This paper studies the risk minimization problem in semi-Markov decision processes with denumerable states. The criterion to be optimized is the risk probability (or risk function) that a first passage time to some target set doesn't exceed a threshold value. We first characterize such risk functions and the corresponding optimal value function, and prove that the optimal value function satisfies the optimality equation by using a successive approximation technique. Then, we present some properties of optimal policies, and further give conditions for the existence of optimal policies. In addition, a value iteration algorithm and a policy improvement method for obtaining respectively the optimal value function and optimal policies are developed. Finally, two examples are given to illustrate the value iteration procedure and essential characterization of the risk function.     

On the Hamiltonicity Gap and doubly stochastic matrices

We consider the Hamiltonian cycle problem embedded in singularly perturbed (controlled) Markov chains. We also consider a functional on the space of stationary policies of the process that consists of the (1,1)‐entry of the fundamental matrices of the Markov chains induced by these policies. We focus on the subset of these policies that induce doubly stochastic probability transition matrices which we refer to as the “doubly stochastic policies.” We show that when the perturbation parameter, ε, is sufficiently small, the minimum of this functional over the space of the doubly stochastic policies is attained at a Hamiltonian cycle, provided that the graph is Hamiltonian. We also show that when the graph is non‐Hamiltonian, the above minimum is strictly greater than that in a Hamiltonian case. We call the size of this difference the “Hamiltonicity Gap” and derive a conservative lower bound for this gap. Our results imply that the Hamiltonian cycle problem is equivalent to the problem of minimizing the variance of the first hitting time of the home node, over doubly stochastic policies. © 2008 Wiley Periodicals, Inc. Random Struct. Alg., 2009