两主两从博弈下的装备维修器材供应链协调研究

以相互竞争的两条装备维修器材供应链作为研究背景,提出了一种基于Stackelberg主从博弈的激励协调模型,并通过最优反应动态思想给出求解该模型的一般思路,结合粒子群优化算法对军事算例进行仿真,对比分析供应商合作与非合作下的计算结果,供应商非合作下奖金激励策略可以有效实现供应链协调,但供应商若能实现合作,将使供应商达到利益最优化,可忽略奖金激励的影响.     

基于MC的电子对抗情报系统ESCPN模型性能分析

针对基本Petri网对电子对抗情报系统描述能力不够的缺点,采用层次化的结构和面向对象的思想,提出一种扩展的随机着色Petri网（Extended Stochastic Coloured PetriNet,ESCPN）模型。对Petri网结构、建模元素、执行规则等进行扩充,分析基于MC状态方程的各项性能指标,以电子对抗情报系统中的初级电子目标生产子系统ESCPN模型为例,应用所建立的性能指标对系统的时间性能进行分析。分析表明,ESCPN模型和连续时间的马尔可夫链（MC）是同构的,能加强模型的描述和分析能力。     

基于多Agent的供应链模型研究

基于多Agent的供应链建模包括分析供应链实体组成、处理流程确定、业务处理Agent设计和业务处理单元框架4层建模．由于Agent具有目标、知识、标识等属性，其通用结构由通讯、业务处理、推理、学习、消息等单元组成．Agent间通信通过基于KQML封装的消息传递．鉴于信息共享是Agent协作的基础，任务分解强调Agent间的交互，故物流和信息流的影响可以通过这两种消息传递的机制得到处理．     

Study on Storage Reliability Evaluation for Ammunition Using Gibbs Sampler

For the gradual maturity of Bayesian survival analysis theory, as well as the defects of the traditional methods for storage reliability evaluation, the Bayesian survival analysis method is proposed to build regression models for reliability in the random truncated test. These models can reflect the influences of different environments on the ammunition storage lifetime. As an example, the common exponential distribution is used here, and Markov chain Monte Carlo（MCMC） method based on Gibbs sampling dynamically simulates the Markov chain of the parameters＇ posterior distribution. Also, the parameters＇ Bayesian estimations are calculated in the random truncated condition. The simulation results show that the proposed method is effective and directly perceived.     

HER扩链剂的合成及其在聚氨酯弹性体中的应用

详细介绍了一种常用的芳香族二醇扩链剂——间苯二酚双（2-羟乙基）醚（HER）的性能特点及3种主要合成方法,概述了HER在浇注型聚氨酯弹性体、热塑性聚氨酯弹性体、高尔夫球材、聚氨酯轮胎、熔纺氨纶、聚氨酯热熔胶等领域的应用情况。     

The effect of uncertainty on the optimal closed-loop supply chain planning under different partnerships structure

In a global economy, the key to success is providing products around the world at the right time in the right quantity and quality, at a low cost. Efficient supply chains have an important role in guaranteeing this success. Optimized planning of such structures is required and uncertainties regarding product demands and prices, amongst other supply chain conditions, should also be considered. In this paper, we look into supply chain planning decisions that account for uncertainty on product portfolios demand and prices. A multi-period planning model is developed where the supply chain operational decisions on supply, production, transportation, and distribution at the actual period consider the uncertainty on products’ demand and prices. Different decision scenarios, involving the evaluation of the supply chain economical performance, are analyzed (e.g. global operating costs/profit realized) for different criteria on the importance of the partners within the global chain (i.e. partners’ structure). A Mixed Integer Linear Programming (MILP) formulation is formulated for each planning scenario and the optimal solution is reached using a standard Branch and Bound (B&B) procedure. The final results provide details on the supply chain partners production, transportation and inventory, at each planning period, while accounting for the importance of each partner in the global chain as well as demand/price uncertainties. The applicability of the developed formulation is illustrated through the solution of a real case-study involving an industrial chain in the pharmaceutical sector.     

3-巯基丁酸酯对MBS树脂相相对分子质量及PVC/MBS力学性能的影响

通过添加3-巯基丁酸酯合成了一系列树脂相相对分子质量变化的甲基丙烯酸甲酯-丁二烯-苯乙烯三元共聚物(MBS树脂)。并将其与聚氯乙烯(PVC)树脂进行熔融共混,测试了PVC/MBS合金的力学性能。结果表明,链转移剂3-巯基丁酸酯用量越多,MBS树脂相的相对分子质量越低,PVC/MBS合金的熔体流动速率越高、加工流动性越好、冲击强度越低,但对拉伸强度影响不大。这对开发系列MBS树脂具有重要指导意义。     

Integration of enterprise levels based on an ontological framework

Enterprises are highly complex systems in which one or more organizations share a definite mission, goals and objectives to offer a product or service. In this study, an ontological framework is built as a mechanism for exchanging information and knowledge models for multiple applications and effective integration between hierarchical levels. The potential of the general semantic framework that is developed is demonstrated using a case study concerning the enterprise supply chain network design-planning problem.     

Mathematical programming and game theory optimization-based tool for supply chain planning in cooperative/competitive environments

This work proposes to improve the tactical decision-making of a supply chain (SC) under an uncertain competition scenario through the use of different optimization criteria, which allows to manage not only the specific objectives of the SC of interest, but also the way how its clients address their selection between different potential suppliers, identifying best market share for the SC of interest and the strategy to attain it. The resulting multi-objective optimization problem has been solved using the ?-constraint method in order to approximate the Pareto space of non-dominated solutions while a framework based on game theory is used as a reactive decision making support tool to deal with the uncertainty of the competitive scenario. The use of the proposed system is illustrated through its application to a multi-product, multi-echelon supply chain case study, which is intended to cooperate or to compete with another SC of similar characteristics.     

灰色-马尔可夫的改进模型及在陶瓷工业产值预测

灰色模型是经济预测方法中最有效的方法之一,但灰色模型对波动性大的序列预测时精度较差.针对这一不足,提出灰色—马尔可夫的改进模型.新模型将原始序列进行对数运算提高数据光滑度,采用距离法降低灰色模型的相对误差,马尔可夫链对预测值进一步修正.将改进模型运用到景德镇陶瓷工业产值预测中,并与传统灰色模型、灰色-马尔可夫模型预测结果进行对比.结果表明改进模型的相对误差远小于灰色模型,预测精度优于灰色-马尔可夫模型,更能反应经济发展趋势.