Inventory models with managerial policy independent of demand

This paper is an extension of two papers. The first of these, published in European Journal of Operational Research, 2007, 112-120 is by Deng et al. (2007) and concerns inventory models for deteriorating items with ramp type demand. The second, published in Computer & Industrial Engineering, 2009, 1296-1300 is by Cheng and Wang (2009) and concerns inventory models for deteriorating items with trapezoidal type demand. The purpose of this paper is threefold. First, this paper will show that the optimal solution is independent of the demand considered in the two previous papers. Second, several replenishment cycles were considered during the finite time horizon, to balance the set-up cost with the sum of the deteriorated cost, holding cost, and shortage cost. Third, this paper will examine the same numerical example in Cheng and Wang (2009) to show that this new approach will result in the saving of 84.39%.     

An efficient computational method for a stochastic dynamic lot-sizing problem under service-level constraints

We provide an efficient computational approach to solve the mixed integer programming (MIP) model developed by Tarim and Kingsman [8] for solving a stochastic lot-sizing problem with service level constraints under the static-dynamic uncertainty strategy. The effectiveness of the proposed method hinges on three novelties: (i) the proposed relaxation is computationally efficient and provides an optimal solution most of the time, (ii) if the relaxation produces an infeasible solution, then this solution yields a tight lower bound for the optimal cost, and (iii) it can be modified easily to obtain a feasible solution, which yields an upper bound. In case of infeasibility, the relaxation approach is implemented at each node of the search tree in a branch-and-bound procedure to efficiently search for an optimal solution. Extensive numerical tests show that our method dominates the MIP solution approach and can handle real-life size problems in trivial time.     

基于期权的树形供应链应急模型与仿真

在多级树形供应链网络环境下,基于实物期权策略并引入中断风险成本,建立了树形供应链应对中断风险的保护与应急模型,通过求解模型得到最优策略并进行了数值仿真分析.仿真结果表明该模型能够显著降低树形供应链系统的中断风险成本与系统中断时间,从而提高供应网络的鲁棒性.     

Support vector machines in water quality management

Support vector classification (SVC) and regression (SVR) models were constructed and applied to the surface water quality data to optimize the monitoring program. The data set comprised of 1500 water samples representing 10 different sites monitored for 15 years. The objectives of the study were to classify the sampling sites (spatial) and months (temporal) to group the similar ones in terms of water quality with a view to reduce their number; and to develop a suitable SVR model for predicting the biochemical oxygen demand (BOD) of water using a set of variables. The spatial and temporal SVC models rendered grouping of 10 monitoring sites and 12 sampling months into the clusters of 3 each with misclassification rates of 12.39% and 17.61% in training, 17.70% and 26.38% in validation, and 14.86% and 31.41% in test sets, respectively. The SVR model predicted water BOD values in training, validation, and test sets with reasonably high correlation (0.952, 0.909, and 0.907) with the measured values, and low root mean squared errors of 1.53, 1.44, and 1.32, respectively. The values of the performance criteria parameters suggested for the adequacy of the constructed models and their good predictive capabilities. The SVC model achieved a data reduction of 92.5% for redesigning the future monitoring program and the SVR model provided a tool for the prediction of the water BOD using set of a few measurable variables. The performance of the nonlinear models (SVM, KDA, KPLS) was comparable and these performed relatively better than the corresponding linear methods (DA, PLS) of classification and regression modeling.     

Visualized study on specific points on demand curves and flow patterns in a single-side heated narrow rectangular channel

A simultaneous visualization and measurement study on some specific points on demand curves, such as onset of nucleate boiling (ONB), onset of significant void (OSV), onset of flow instability (OFI), and two-phase flow patterns in a single-side heated narrow rectangular channel, having a width of 40 mm and a gap of 3 mm, was carried out. New experimental approaches were adopted to identify OSV and OFI in a narrow rectangular channel. Under experimental conditions, the ONB could be predicted well by the Sato and Matsumura model. The OSV model of Bowring can reasonably predict the OSV if the single-side heated condition is considered. The OFI was close to the saturated boiling point and could be described accurately by Kennedy’s correlation. The two-phase flow patterns observed in this experiment could be classified into bubbly, churn, and annular flow. Slug flow was never observed. The OFI always occurred when the bubbles at the channel exit began to coalesce, which corresponded to the beginning of the bubbly–churn transition in flow patterns. Finally, the evolution of specific points and flow pattern transitions were examined in a single-side heated narrow rectangular channel.     

需求率为斜坡型的一类变质性物品最优库存策略

本文在考虑需求率服从斜坡型分布的情况下,研究了允许缺货且缺货完全回补、变质率服从威布尔分布、补货率为无穷、有限计划期内的库存模型,证明了最优补货策略的存在性,并给出了求解最优补货策略的算法.     

需求拉动型供应链突发风险传递模型

研究突发事件风险在需求拉动型供应链中传递的效应和规律。以博弈论思想为指导,分析了突发事件风险在需求拉动型供应链中传递的过程,建立了相应的风险传递模型,计算了供应链双方利润的需求风险弹性系数。研究表明:供应链双方利润与市场容量呈正相关,与价格敏感系数呈负相关;突发事件引起的市场容量变化对供应链双方利润的影响要远大于价格弹性系数变化对供应链双方利润的影响;无论供应链成本如何变化,供应链各方利润对需求总量和需求倾向的各风险弹性系数恒大于1,说明下游需求的小幅变动可能引起上游利润的大幅变动,证明了牛鞭效应的存在。     

A Dynamic Supplier Selection and Inventory Management Model for a Serial Supply Chain with a Novel Supplier Price Break Scheme and Flexible Time Periods

A new supplier price break and discount scheme taking into account order frequency and lead time is introduced and incorporated into an integrated inventory planning model for a serial supply chain that minimizes the overall incurred cost including procurement, inventory holding, production, and transportation. A mixed-integer linear programming (MILP) formulation is presented addressing this multi-period, multi-supplier, and multi-stage problem with predetermined time-varying demand for the case of a single product. Then, the length of the time period is considered as a variable. A new MILP formulation is derived when each period of the model is split into multiple sub-periods, and under certain conditions, it is proved that the optimal solution and objective value of the original model form a feasible solution and an upper bound for the derived model. In a numerical example, three scenarios of the derived model are solved where the number of sub-period is set to 2, 3, and 4. The results further show the decrease of the optimal objective value as the length of the time period is shortened. Sufficient evidence demonstrates that the length of the time period has a significant influence on supplier selection, lot sizing allocation, and inventory planning decisions. This poses the necessity of the selection of appropriate length of a time period, considering the trade-off between model complexity and cost savings.     

Optimal consumption and investment with insurer default risk

We solve the optimal consumption and investment problem in an incomplete market, where borrowing constraints and insurer default risk are considered jointly. We derive in closed-form the optimal consumption and investment strategies. We find two main results by quantitative analysis. As insurer default risk increases, the proportion of wealth invested in stocks could increase when wealth is small, and decrease when wealth is large. As risk aversion increases, the voluntary annuity demand could increase when insurer default risk is low, and decrease when this risk is high.     

An in-service primary teacher’s implementation of mathematical tasks: the case of length measurement and perimeter instruction

The purpose of this paper is to examine the cognitive demand levels of tasks used by an in-service primary teacher during length measurement and perimeter instruction and to examine a possible link between these tasks and the teacher’s mathematical knowledge in teaching. For this purpose, a case study approach was used and the data was drawn from classroom observations, semi-structured interviews, and field notes. Specific tasks from length measurement and perimeter instruction were presented and analyzed according to the Mathematical Tasks Framework. Then, how these tasks gave information about the teacher’s mathematical knowledge in teaching in the length measurement and perimeter topics was examined according to the Knowledge Quartet model. According to the findings of the study, the tasks used during length measurement and perimeter instruction were mostly categorized as low-level tasks. In addition, teacher’s mathematical knowledge in teaching affected the implementation of the tasks.