Computing globally optimal (s,S,T) inventory policies

We consider a single-echelon inventory installation under the (s,S,T) periodic review ordering policy. Demand is stationary random and, when unsatisfied, is backordered. Under a standard cost structure, we seek to minimize total average cost in all three policy variables; namely, the reorder level s, the order-up-to level S and the review interval T. Considering time to be continuous, we first model average total cost per unit time in terms of the decision variables. We then show that the problem can be decomposed into two simpler sub-problems; namely, the determination of locally optimal solutions in s and S (for any T) and the determination of the optimal T. We establish simple bounds and properties that allow solving both these sub-problems and propose a procedure that guarantees global optimum determination in all policy variables via finite search. Computational results reveal that the usual practice of not treating the review interval as a decision variable may carry severe cost penalties. Moreover, cost differences between (s,S,T) and other standard periodic review policies, including the simple base stock policy, are rather marginal (or even zero), when all policies are globally optimized. We provide a physical interpretation of this behavior and discuss its practical implications.     

Salient Value Similarity, Social Trust, and Risk/Benefit Perception

It was postulated that shared values determine social trust in institutions and persons related to a technology: One has trust in people holding similar salient values. Furthermore, it was hypothesized that social trust has a positive influence on perceived benefits and a negative impact on perceived risks. Results of a survey of University of Zürich students indicated that the proposed causal model explained perception of pesticides, nuclear power, and artificial sweetener very well. When social trust was controlled, the relation between risks and benefits perceived diminished. Results indicate that social trust is a key predictive factor of the perceived risks and benefits of a technology, and provide support for the salient values similarity theory of social trust.     

中国A股公司市盈率、市净率与ROE水平的关系研究

本文利用沪深两市1996年至2002年A股公司的数据,全面系统地研究了ROE水平与市盈率、市净率间的关系,分析了市盈率和市净率作为估值标准的合理性问题.检验结果表明,市净率与ROE水平间是非单调的函数关系,合理地反映了不同ROE水平公司未来业绩、风险和净资产的质量等基本面因素,是理想的估值标准;而市盈率受盈余管理影响很大,不是恰当的估值标准.     

Job-shop scheduling-joint consideration of production,transport, and storage/retrieval systems

This paper proposes a new problem by integrating the job shop scheduling, the part feeding, and the automated storage and retrieval problems. These three problems are intertwined and the performance of each of these problems influences and is influenced by the performance of the other problems. We consider a manufacturing environment composed of a set of machines (production system) connected by a transport system and a storage/retrieval system. Jobs are retrieved from storage and delivered to a load/unload area (LU) by the automated storage retrieval system. Then they are transported to and between the machines where their operations are processed on by the transport system. Once all operations of a job are processed, the job is taken back to the LU and then returned to the storage cell. We propose a mixed-integer linear programming (MILP) model that can be solved to optimality for small-sized instances. We also propose a hybrid simulated annealing (HSA) algorithm to find good quality solutions for larger instances. The HSA incorporates a late acceptance hill-climbing algorithm and a multistart strategy to promote both intensification and exploration while decreasing computational requirements. To compute the optimality gap of the HSA solutions, we derive a very fast lower bounding procedure. Computational experiments are conducted on two sets of instances that we also propose. The computational results show the effectiveness of the MILP on small-sized instances as well as the effectiveness, efficiency, and robustness of the HSA on medium and large-sized instances. Furthermore, the computational experiments clearly shown that importance of optimizing the three problems simultaneous. Finally, the importance and relevance of including the storage/retrieval activities are empirically demonstrated as ignoring them leads to wrong and misleading results.

     

Loss/Gain Framing,Dose, and Reactance: A Message Experiment

Whether a loss or gain frame has a persuasive advantage in communicating health risks is a matter of ongoing debate. Findings reported in the literature are mixed, suggesting that framing effects are likely complex and may be influenced by a combination of factors. This study examined reactance as a mediator and dose as a moderator of loss/gain framing effects. Adults (N = 1,039) read framed messages about the health consequences of physical (in)activity in varying message doses (i.e., number of framed statements). Compared to loss frames, gain frames generated more threat to freedom and reactance. Dosage exerted significant influence at the extremes; the one‐dose messages invoked less intentions to exercise compared to the four‐dose messages. Planned contrasts revealed significant frame × dose interactions. Notably, the one‐dose gain‐framed messages triggered significantly more freedom threat and less intentions to engage in physical activity—a situation that changed when the information was loss‐framed or when the dosage was increased.     

Earliness/Tardiness Production Scheduling and Planning,and solutions

Earliness/Tardiness Production Planning (ETPSP) has attracted much attention in recent years. In practice, it provides an efficient way to integrate Manufacturing Resource Planning (MRP-II) Scheduling and with Just-In Time (JIT). Conventional research mainly focused on the condition of single-machine and parallel multi-machine. Capacity balance has not been considered. Some investigations of existing research on ETPSP are given in this paper. An extensive model of ETPSP with consideration of multi-process capacity balance for manufacturing systems is proposed. Two alternative solutions, key-process method and relaxation method, are both developed to solve ETPSP. Computational results identify that both methods are powerful to solve ETPSP which minimizes total earliness and tardiness penalties. Furthermore, some comparisons between these two methods and other conventional methods indicate the efficiency of the former.