A quantity discount approach to supply chain coordination

Quantity discounts provide a practical foundation for inventory coordination in supply chains. However, typical supply chain participants may encounter difficulties in implementing the coordination policy simply because (1) specified lot size adjustments may deviate from the economic lot sizes and (2) the buying firm may face amplified overstocking risks related to increased order quantities. The main objective of this study is to develop a quantity discount model that resolves the practical challenges associated with implementing quantity discount policies for supply chain coordination between a supplier and a buyer. The proposed Buyer’s Risk Adjustment (B-RA) model allows the supplier to offer discounts that capitalize on the original economic lot sizes and share the buyer’s risk of temporary overstocking under uncertain demand. The analytical results suggest that the proposed B-RA discount approach is a feasible alternative for supply chain coordination under uncertain demand conditions.     

食饵具有流行病的阶段结构捕食模型

本文考虑了一类食饵具有流行病和阶段结构的脉冲时滞捕食模型．利用脉冲时滞微分方程的相关理论和方法，获得易感害虫根除周期解全局吸引的充分条件以及当脉冲周期在一定范围内时，天敌与易感害虫可以共存且易感害虫的密度可以控制在经济危害水平E（EIL）之下．我们的结论为现实的害虫管理提供了可靠的策略依据．     

Multi-mode project payment scheduling problems with bonus–penalty structure

This paper involves the multi-mode project payment scheduling problem with bonus–penalty structure where activities can be performed with several modes and a bonus–penalty structure exists at the deadline of the project. In the problem the decisions on when to schedule events and payments, the magnitude of each payment, and the performing mode of each activity need to be optimized. A two-module simulated annealing heuristic is proposed to solve the mixed integer non-linear programming models for the contractor and the client, and a satisfactory solution, which consists of payment event set, event schedule, and payment amount set, may be found through iterations between the heuristic’s two modules. The profits of the two parties of the contract are changed significantly by the bonus–penalty structure and the structure may be considered as a coordination mechanism essentially, which may enhance the flexibility of payment scheduling and be helpful for the two parties to get more profits from the project. Through solving and analyzing an instance the insight that the bonus–penalty structure may advance the project completion effectively and improve the profits of the two parties in the meantime can be obtained.     

组合导航系统初始对准的稳定性分析及其控制

针对INS/GPS组合导航系统的初始对准问题，说明当载体受到周期性激励时（由风浪、地面振动等因素引起），状态变量的估计结果也会出现周期性振荡，从而影响系统状态变量的估计精度，通过仿真说明了利用线性反馈可以消除周期性激励对系统的影响。     

A heuristic for single-warehouse multiretailer supply chains with all-unit transportation cost discounts

In supply chain management research, transportation costs, if explicitly considered at all, are frequently assumed to be linear. These costs often have a more complex form, such as an all-unit discount structure – this piecewise cost function adds significant complexity when included in supply chain management problems and is therefore often ignored due to solution time or tractability concerns. We present and evaluate a new heuristic procedure which provides good solutions to problems involving all-unit discount cost functions while significantly reducing solution times. The general nature of this procedure does not require assumptions about the supply chain structure or policies, and is therefore applicable in a wide range of settings.     

MaxVaR with non-Gaussian distributed returns

The common fallacy in risk measurement throughout a long investment horizon is to handle only the terminal risk. This pathology affects Value-at-Risk, hence a recent contribution in the literature has proposed the concept of within-horizon risk as a solution to the problem. The quantification of this type of risk leads to the so called MaxVaR measure, but the assumption of Gaussian distributed returns biases this model. This study analyzes the consequences of non-Gaussian returns to the MaxVaR inference. An example of application to long-term risk management is provided.     

气温随机模型与我国气温期权定价研究

建立气温期权交易对于对冲天气风险,增加市场金融投资品种具有重要意义。本文主要参照均值回复模型,考虑气温的季节变化和长期趋势,建立反映气温变化的随机模型,应用1980至1999年北京日平均气温对模型参数进行估计。实证仿真以及模型验证结果表明,模型的相对误差较小,建立的气温随机模型能够对未来气温变化进行较好的模拟。蒙特卡罗方法能够对天气衍生产品进行合理定价。     

Optimal harvesting policy of an inland fishery resource under incomplete information

A new mathematical model for finding the optimal harvesting policy of an inland fishery resource under incomplete information is proposed in this paper. The model is based on a stochastic control formalism in a regime‐switching environment. The incompleteness of information is due to uncertainties involved in the body growth rate of the fishery resource: a key biological parameter. Finding the most cost‐effective harvesting policy of the fishery resource ultimately reduces to solving a terminal and boundary value problem of a Hamilton‐Jacobi‐Bellman equation: a nonlinear and degenerate parabolic partial differential equation. A simple finite difference scheme for solving the equation is then presented, which turns out to be convergent and generates numerical solutions that comply with certain theoretical upper and lower bounds. The model is finally applied to the management of Plecoglossus altivelis, a major inland fishery resource in Japan. The regime switching in this case is due to the temporal dynamics of benthic algae, the main food of the fish. Model parameter values are identified from field measurement results in 2017. Our computational results clearly show the dependence of the optimal harvesting policy on the river environmental and biological conditions. The proposed model would serve as a mathematical tool for fishery resource management under uncertainties.     

传统解剖学特征与深度学习相结合的肺叶分割算法

CT图像中肺叶位置的确定对于肺部疾病的准确定位以及定性定量分析具有重要意义。为了提高肺叶自动分割准确率,提出了一种结合气管,血管等传统解剖学特征以及深度学习的肺叶分割算法。对原始图像进行预处理,获取肺实质、气管、血管以及基于深度学习网络的肺裂分割结果;整合来自多个解剖结构的信息生成分水岭分割所需成本图像;通过基于深度学习网络的肺叶粗分割结果,获取肺叶标记区域;执行基于标记的分水岭分割,实现肺叶的自动分割。选取了来自上海市肺科医院的20例含有肺部疾病患者的CT图像对该方法进行验证,最终的Jaccard相似性系数为92.4%。实验结果表明方法具有较高的肺叶分割精度,并且具有较强的鲁棒性。     

Capturing and prioritizing students’ requirements for course design by embedding Fuzzy-AHP and linear programming in QFD

Customer requirements play a vital and important role in the design of products and services. Quality Function Deployment (QFD) is a popular, widely used method that helps translate customer requirements into design specifications. Thus, the foundation for a successful QFD implementation lies in the accurate capturing and prioritization of these requirements. This paper proposes and tests the use of an alternative framework for prioritizing students’ requirements within QFD. More specifically, Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) and the linear programming method (LP-GW-AHP) based on Data Envelopment Analysis (DEA) are embedded into QFD (QFD-LP-GW-Fuzzy AHP) in order to account for inherent subjectivity of human judgements. The effectiveness of the proposed framework is assessed in capturing and prioritizing students’ requirements regarding courses’ learning outcomes within the process of an academic course design. Sensitivity analysis evaluates the robustness of the prioritization solution and implications for course design specifications are discussed.