基于CVaR准则的Newsboy型商品最优广告费用与订货策略

研究了风险厌恶型零售商在面对随机市场需求与广告投入相关时的最优广告投入与订货策略. 通过乘法需求形式将广告投入对需求的影响引入Newsboy问题中, 并以CVaR作为风险度量准则, 建立了风险厌恶型零售商广告投入与订货量联合决策的随机模型; 揭示了风险厌恶程度、需求不确定性以及商品本身特性对零售商最优广告投入和订货量的影响; 最后通过应用实例对理论结果进行了验证分析. 研究结果为零售商制订广告投入策略和相应的订货策略提供了参考.     

单供应商多零售商供应链中的最优提前订货折扣

零售商提前订货是一种供应链协调策略,即零售商向供应商订货时,订货提前期大于从供应商到零售商的正常的供货提前期.本文讨论一个由单一供应商和多个零售商组成的供应链,其中供应商采用基于提前订货时段的折扣方法引导零售商提前订货.通过建立相应的数学模型,分析了零售商如何确定提前订货的最佳时段,以及供应商如何确定最优的折扣方案.     

基于数量折扣的时滞变质物品库存协调模型

建立了单个生产商和单个零售商的斯坦伯格博弈模型, 生产商以固定生产率生产一种时滞变质物品, 零售商面对依赖价格和时间的需求. 首先, 分别给出了分散、集中情况下价格和订货批量的均衡解, 并通过数值算例分析得出, 批发价格随着易逝率增加而减小, 随着产品可维持其原有品质的时间的增加而增加; 易逝率较大时, 零售价格随着产品可以维持其原有品质的时间增加而减小; 然而易逝率较小时, 零售价格随着产品可以维持其原有品质的时间增加而增加. 其次, 给出使系统达到最优的数量折扣契约, 通过数值分析得出订货批量增值会随着产品可维持其原有品质时间增加而增加; 价格敏感系数、生产成本增加时, 批发价格折扣的Pareto上下限均会变大. 最后, 通过分析得出, 生产商向零售商提供的最优批发价格折扣随着生产商的生产成本和库存持有成本增加而增加.     

运力合同在货运业中的应用价值研究

期权合同和固定承诺合同是货运应用中的两类重要合同,已有研究多从承运企业的角度分析两类合同对海运链的协调作用.本文从货运代理的角度出发研究合同市场和现货市场并存的情况下两类货运合同的应用价值,根据改进的报童模型分析了多阶段模型下针对两类货运合同的货运代理最优运力预订策略和运力执行策略,并在此基础上分析了合同的灵活性价值.进一步研究了期权的执行时序对两类合同应用价值及期权合同灵活性的影响.研究结果表明,在两类信息模式下货运代理最优合同选择都是期权合同,而且合同执行时序滞后降低了现货价格信息不确定性,提高了期权合同的应用价值.     

存在策略消费者的动态定价策略

在线零售商能够方便地提供历史价格和未来价格预期以供消费者参考,但这种为消费者提供的便利同时给零售商的动 态定价带来困难,聪明的消费者会根据未来产品的价格以及历史参考价格做出购买与否的判断,给零售商的利润带来很大的 影响. 论文将消费者的策略性行为和参考价格效应结合,准确地描述消费者在历史和预期价格影响下零售商的动态定价策略,建立了多阶段动态定价策略模型,并针对两阶段简化为正常价和清仓价的模型,给出两种不同的价格策略以及实施的前提条件,讨论了两阶段最优价格和期望最大利润跟消费者效用折扣因子、策略性消费者所占比例、消费者对历史价格的依赖程度的关系,结论表明忽视消费者策略行为以及价格参考效应会给零售商带来较大的负面影响.     

现货市场异常波动下股指期货交易限制对市场质量的影响分析

通过计算机仿真构建了基于投资者策略的跨市场金融平台,提出了异常波动下交易限制措施对市场质量的评价体系.从股指期货交易限制的角度,研究在现货市场异常波动期间管制措施对期货和现货市场质量的影响,并比较在不同的市场结构下管制措施的有效性.研究发现,对于股指期货的交易限制措施在短期内有效,但中长期内无法发挥股指期货基本功能.另外,交易限制的短期效果在一个新进杠杆资金较少的市场上是最好的,而在中长期市场中适当增加的投机和套利活动能抵消交易限制措施的效果,为市场提供流动性,使市场更快恢复到原来的状态.因此,异常波动下的股指期货交易限制应该是临时性的,在市场企稳后应该及时逐步恢复原有的制度结构.     

混合经济增长模型中的最优财政政策

在已有含人力资本的内生经济增长理论模型的基础上,提出一般化的混合经济内生增长模型.该模型适用于从理论上考察适应我国社会主义市场经济发展的最优宏观政策.从不同与以往的增长动态分析的视角,探讨了当人力资本存在外溢效应时、政府可否通过适当的财政政策引导经济达到社会性的最优增长状态,导出了关于征税和财政补贴的最优性条件并探讨了它们的政策含意.     

天波超视距雷达缺损信号的频谱重构

天波超视距雷达(over the horizon radar, OTHR)电波通过电离层折射作下视探测,具有观察距离远、观察范围广、反隐身等特点。但由于OTHR通常采用HF频段,电波传播环境复杂,回波存在很强的瞬态干扰。对OTHR信号的瞬态干扰抑制导致信号缺损。同时,现代OTHR需要多目标海空兼容工作,也导致回波信号的非均匀连续采样。针对OTHR信号的部分缺损问题,提出了基于稀疏信号处理的完整频谱重建算法。算法中将OTHR稀缺信号的频谱重建问题转化为一个范数1优化函数的求解问题,直接获得信号的完整频谱。利用仿真和实测数据分别对干扰和非连续采样导致的缺损信号进行频谱恢复,结果验证了算法的有效性。     

AN ALGORITHM FOR THE DETERMINATION OF THE ECONOMIC ORDER QUANTITY IN A TWO-LEVEL SUPPLY CHAIN WITH TRANSPORTATION COSTS： COMPARISON OF DECENTRALIZED WITH CENTRALIZED DECISION

This paper considers a two-level supply chain consisting of one warehouse and one retailer. In this model we determine the optimal ordering policy according to inventory and transportation costs. We assume that the demand rate by the retailer is known. Shortages are allowed neither at the retailer nor at the warehouse. We study this model in two cases; decentralized and centralized. In the decentralized case the retailer and the warehouse independently minimize their own costs; while in the centralized case the warehouse and the retailer are considered as a whole firm. We propose an algorithm to find economic order quantifies for both the retailer and the warehouse which minimize the total system cost in the centralized case. The total system cost contains the holding and ordering costs at the retailer and the warehouse as well as the transportation cost from the warehouse to the retailer. The application of this model into the pharmaceutical downstream supply chain of a public hospital allows obtaining significant savings. By numerical examples, the costs are computed in MATLAB to compare the costs in the centralized case with decentralized one and to propose a saving-sharing mechanism through quantity discount.     

一类切换时滞奇异系统的最优保成本控制

针对一类切换时滞奇异系统,对最优保成本控制问题进行了研究。利用Lyapunov函数方法和凸组合技术,给出了由线性矩阵不等式(linear matrix inequality, LMI)表示的保成本控制器存在的充分条件,并设计了相应的子控制器和切换规则。进一步,建立了一个具有线性矩阵不等式约束的凸优化问题,利用Matlab软件中的线性矩阵不等式工具箱求解,给出了最优保成本控制器的设计方法及闭环最小性能指标上界。仿真示例验证了该方法的有效性。     

Fundamentals of the analytic network process — Dependence and feedback in decision-making with a single network

The Analytic Network Process (ANP) is a multicriteria theory of measurement used to derive relative priority scales of absolute numbers from individual judgments (or from actual measurements normalized to a relative form) that also belong to a fundamental scale of absolute numbers. These judgments represent the relative influence, of one of two elements over the other in a pairwise comparison process on a third element in the system, with respect to an underlying control criterion. Through its supermatrix, whose entries are themselves matrices of column priorities, the ANP synthesizes the outcome of dependence and feedback within and between clusters of elements. The Analytic Hierarchy Process (AHP) with its independence assumptions on upper levels from lower levels and the independence of the elements in a level is a special case of the ANP. The ANP is an essential tool for articulating our understanding of a decision problem. One had to overcome the limitation of linear hierarchic structures and their mathematical consequences. This part on the ANP summarizes and illustrates the basic concepts of the ANP and shows how informed intuitive judgments can lead to real life answers that are matched by actual measurements in the real world (for example, relative dollar values) as illustrated in market share examples that rely on judgments and not on numerical data. Thomas L. Saaty holds the Chair of University Professor, Katz Graduate School of Business, University of Pittsburgh, Pittsburgh, PA, and obtained his Ph.D. in mathematics from Yale University. Before that he was a professor at the Wharton School of the University of Pennsylvania for ten years. Prior to that he spent seven years at the Arms Control and Disarmament Agency in the State Department in Washington, DC, that carried out the arms reduction negotiations with the Soviets in Geneva. His current research interests include decision-making, planning, conflict resolution and synthesis in the brain. As a result of his search for an effective means to deal with weapons tradeoffs at the Disarmament Agency and, more generally, with decision-making and resource allocation, Professor Saaty developed The Analytic Hierarchy Process (AHP) and its generalization to dependence and feedback, the Analytic Network Process (ANP). He is co-developer of the software Expert Choice and of the software Super Decisions for decisions with dependence and feedback. He has authored or co-authored twelve books on the AHP/ANP. Professor Saaty has also written a number of other books that embrace a variety of topics, including Modern Nonlinear Equations, Nonlinear Mathematics, Graph Theory, The Four Color Problem, Behavioral Mathematics, Queuing Theory, Optimization in Integers, Embracing the Future and The Brain: Unraveling the Mystery of How It Works. His most recent book is Creative Thinking, Problem Solving & Decision Making. The book is a rich collection of ideas, incorporating research by a growing body of researchers and practitioners, profiles of creative people, projects and products, theory, philosophy, physics and metaphysics...all explained with a liberal dose of humor. He has published more than 300 refereed articles in a wide variety of professional journals. He has been on the editorial boards of Mathematical Reviews, Operations Research, Naval Research Logistics Quarterly, Mathematical and Computer Modeling, Socio-Economic Planning Sciences, Applied Mathematics Letters, and several others. He also served as consultant to many corporations and governments.     

感知质量差异对网络外部性市场结构演化的影响

运用演化经济理论研究消费者感知质量差异对网络外部性市场结构演化的影响.研究结果表明:不同消费者对新产品感知质量的差异是驱动网络外部性市场演化的重要因素,在一定程度上决定了市场演化结果呈现为赢家通吃或新旧产品共存.当感知质量差异明显时,市场演化的均衡结果通常是新旧产品共存,且新产品占据市场主流;当感知质量差异不明显时,市场演化结果总是赢家通吃.在技术创新速度很快且产品质量与产品网络效应强度相关程度很高的条件下,市场出现锁定,旧产品继续占据整个市场,反之则新产品完全替代旧产品.这些结论有助于网络外部性市场中企业制定有效的新产品策略.     

存在基站误差的稳健时差定位算法

针对存在基站误差的目标无源定位问题,提出了一种基于修正牛顿算法的时差定位技术。众所周知,牛顿法对初值要求较高,较差初值会导致迭代发散,而且基站位置误差也会导致牛顿算法Hessian矩阵维数扩大和目标函数的缓慢下降,使运算量变大。该算法利用最大似然方法确定目标函数,运用牛顿法对目标位置进行迭代求解,对于计算过程中可能出现的病态Hessian矩阵,引入正则化理论修正病态的Hessian矩阵,使保证迭代收敛,同时简化算法降低Hessian矩阵的维数并且加速目标函数的下降趋势,使目标位置解脱离局部最小值,算法能够稳健高效的运行。实验结果表明:相对于传统牛顿法,此算法在初始值的选取上具有稳健性,对误差选取较大的初始值,仍能够保证算法的收敛性,同时加速了收敛速度,降低了计算量;相对于现有闭合式定位方法,此算法在噪声较大时具有较好的定位精度。     

考虑近区多重散射的目标RCS图形电磁算法

计算目标雷达散射截面时,对于存在近区多次散射的目标,对存在近区耦合场的单元的识别非常复杂。从磁场积分方程出发,结合图形电磁计算平台GRECO,经过适当的坐标转换,可快速识别对单元产生耦合场的区域;同时,采用迭代物理光学方法,计算了典型目标的近场与远场RCS。数值算例证明了本方法的有效性,本方法考虑了目标的多重散射特性,使得图形电磁计算方法从物理光学方法扩展应用到迭代物理光学方法。     

区间数据典型相关分析技术及其在股市分析中的应用

采用一种针对大规模复杂数据的分析技术——符号数据分析方法(SymbolicDataAnalysis简称SDA),以中信证券风格指数作为研究对象,对2002年中国股票市场的财务指标与市场表现进行典型相关分析.研究结果表明,中国股市财务状况与市场表现相关性明显,上市公司的收益状况、偿债能力、资金管理能力及价值/成长因素决定股票的运行状况,不同风格股票在财务-市场关系方面差异性显著,行业特征明显.通过分析可以看到,运用符号数据对中国股市运行特征进行的分析结论与客观现实非常吻合,从而证明使用符号数据的典型相关分析技术对大规模多维动态数据系统进行统计分析是十分有效的.     

基于非线性相依的市场间金融传染度量——测度2015年中国股灾对重要经济体的传染效应

针对真实市场间所具有的非线性、尾部极值相依性及时变性等相依特征,本文以2015年6月中国爆发的股灾为背景,从传染效应的存在性、传染强度、传染方向三个视角深入研究中国股市对日本、美国、韩国三个重要经济体股市的金融传染效应.首先,将极值理论(extreme value theory,EVT)与时变Clayton Copula函数相结合构建时变Clayton Copula-EVT模型,估计下尾极值动态相依系数,并进行统计检验,发现中国股市对日本、美国股市存在风险传染效应,而对韩国股市不存在风险传染效应;进一步地,量化中国股市对日本、美国股市的风险传染强度,发现中国股市对日本、美国股市的传染强度都较大,且中国股市对美国股市的传染强度明显强于其对日本股市的传染强度;最后,利用基于时间延迟的去趋势交叉相关性分析方法研究中国股市与日本、美国股市之间的风险传染方向,发现股灾后市场间风险传导方向发生了改变,风险主要由中国股市传染至日本、美国股市.上述实证结果为深入研究市场间金融风险传染的非线性相依特征机理提供了有益的参考.     

ADVANCES IN DECISION ANALYSIS AND SYSTEMS ENGINEERING FOR MANAGING LARGE-SCALE ENTERPRISES IN A VOLATILE WORLD： INTEGRATING BENEFITS, OPPORTUNITIES, COSTS AND RISKS （BOCR） WITH THE BUSINESS MOTIVATION MODEL （BMM）

1. Introduction Recent advances in Information and Communication Technologies (ICT) have occurred in a number of areas includinginformation quality (Chutimaskul and Wangpipatwong 2004), strategy (Sha, Hung and Lin 2004) organization (Crowne 2004), technological change (Mitchell 2004), and utility1. Introduction Recent advances in Information and Communication Technologies (ICT) have occurred in a number of areas includinginformation quality (Chutimaskul and Wangpipatwong 2004), strateg…     

Tracking performance of large margin classifier in automatic modulation classification with a software radio environment

Automatic modulation classification is the process of identification of the modulation type of a signal in a general environment. This paper proposes a new method to evaluate the tracking performance of large margin classifier against signal-tonoise ratio （SNR）, and classifies all forms of primary user＇s signals in a cognitive radio environment. For achieving this objective, two structures of a large margin are developed in additive white Gaussian noise （AWGN） channels with priori unknown SNR. A combination of higher order statistics and instantaneous characteristics is selected as effective features. Simulation results show that the classification rates of the proposed structures are well robust against environmental SNR changes.     

协同学与我国可持续发展系统自组织研究

可持续发展系统 (SDS)是人类社会赖以存在和发展的巨系统 ,是开放的合作的自组织系统。在我国可持续发展对策研究中 ,运用协同学 ,研究可持续发展系统 (SDS)中各子系统之间是怎样合作以产生宏观的空间结构、时间结构或功能结构的 ,找出可持续发展系统 (SDS)的自组织演化规律 ,对促进可持续发展的协同有序具有十分重要的作用。