报童投资组合模型中的批发价契约设计

当风险规避型报童的订货资金有限,却有多种产品可供订购时,供应商需要设计恰当的契约,以引导报童的订货行为,实现最大化自身收益的目的。针对上述问题,本文运用投资组合理论处理报童的决策问题;在此基础上建立了供应商与报童之间的博弈模型,设计了求解最优批发价契约的算法;通过数值算例,说明了最优契约的求解过程。结果表明,与未经优化而随机选择的契约相比,基于该算法求得的契约显著提升了供应商的期望收益。     

证券投资组合决策模型的应用研究

马科威茨投资组合模型建立在单目标规划的基础上,投资者固定一个目标使另一个目标达到最优。然而,理性的投资者总是追求收益尽可能大,风险尽可能小的投资组合。文章利用多目标规划的方法,建立了证券投资组合的多目标规划模型,引入偏好系数将其转化为可根据投资者偏好决定投资方案的模型,同时利用遗传算法对模型进行求解。     

基于Portfolio的公司项目投资战略决策分析

针对公司项目投资规划方案的风险评估和决策问题,根据项目的投资收益,建立了项目投资收益评估模型;引入了战略环境概念,通过其概率分布来描述公司内外战略环境发展的不确定性,并在此基础上,以综合收益率均值和衡量风险程度的方差σ20作为项目投资规划方案的评估指标;应用资产组合理论建立了最优风险决策模型。     

带有缺货损失的报童模型的利润与风险的均衡分析

报童模型中,当有缺货损失时,零售商的最优定货量会受到一定的影响,且这个影响还依赖于需求的分布、单位缺货惩罚的大小等因素。本文研究了需求量为指数分布下带有缺货损失的报童模型的期望利润与亏损风险的均衡分析。     

强制减排和碳偏好影响下的制造商产能决策

为了研究在政府给定碳排放总量的约束下,面临随机需求的制造商的产能决策问题,在改进报童模型的基础上,比较了碳排放总量约束前后的制造商最优产量和单位产品减排量的变化,发现了排放总量约束使得最优产量减少。然后,在市场减排努力函数拉动需求的前提下,给出了制造商的最优产量和单位产品减排量之间的关系式,并且证明了减排努力函数可以是任意线性函数或者非线性的凹函数。最后通过算例分析印证了结论。     

大规划定制模式下基于粗模糊集的定制方案多目标评价模型

针对大规模定制模式下的定制方案评价这一典型的多目标决策问题,提出了基于粗模糊集的定制方案多目标评价模型及算法,并对建模过程的主要步骤和关键问题作了阐述:收集并处理定制的历史记录从而构造决策表;利用粗糙逻辑和决策方法对已有知识进行逻辑的推演与分析,提取相应的最优决策规则;最后,利用粗糙分类和模糊评价的集成算法实现定制方案评价的工作过程。     

多因素影响下的最优年金化时间决策

长寿风险是退休计划中易被低估的风险因素,这类风险因人类寿命的不断延长而快速增大。养老年金具有规避长寿风险和提高消费者效用的双重价值,在养老保障中具有重要的作用。本文系统考虑退休计划中消费者的寿命风险和遗赠需求,讨论年金投资中的最优年金化时间决策,通过构建单周期的最优年金化时间选择模型,分析了消费者在整个退休计划中如何进行年金投资这一多期决策问题。本文最后展示了不同参数设置下的计算结果,以说明消费者的遗赠需求强度与风险厌恶特征、年金管理费率、年金收益与风险水平等因素对最优年金化时间的影响。     

满意准则模型应用研究

由于世界各国法规对汽车安全性提出了越来越高的要求,人们开始重视对汽车乘员约束系统优化工作。而汽车安全带是乘员约束系统的重要组成部分,是汽车驾驶员和乘员的重要保护装置,所以对安全带特性的研究工作在国内外仍在继续进行。乘员约束系统逆问题满意准则模型是本文作者提出的新数学模型,它反映了汽车CAE的实际需要。该模型抛弃了寻求多目标问题最优解（或权衡最优解）的思维方式,以决策者满意为准则,寻求多目标问题的满意解。本文利用该模型,以头部伤害指标和胸部伤害指标为评价指标,利用汽车碰撞模拟软件MADYMO进行数学试…     

基于线性规划的不同项目投资额的确定

主要运用线性规划方法,确定各项目的投资额,实现最优的项目组合,从而满足投资方收益最大化或风险最小化的投资目标.主要利用了管理运筹学2.0版软件,求解线性规划问题的最优解,并进行了灵敏度分析.     

双资产最优投资组合

均值方差模型是在金融中最常用的模型,通过均值方差模型,能够合理地将资金进行投资达到在一定风险下获取最大的收益.本文对双资产均值方差模型进行深入探讨,并且谈论最优权重存在的条件和意义.     

Modeling technological innovation risks of an entrepreneurial team using system dynamics: An agent-based perspective

Continuous technological innovation has been playing a vital role in ensuring the survival and development of an enterprise in today's economy. This paper studies the problem of technological innovation risk-based decision-making from an entrepreneurial team point of view. We identify the differences between this team decision-making and a traditional individual decision-making problem, where decisions are mainly affected by the decision-maker's risk and value perceptions, and risk preferences. We create a modeling framework for such a new problem, and use system dynamics theory to model it from the agent-based modeling perspective. The proposed approach is validated by a case study of the technological innovation risk decision-making in a Chinese automobile company.     

A multi-period portfolio selection optimization model by using interval analysis

Due to few historical data that can be obtained in an emerging securities market, the future returns, risk and liquidity of securities cannot be forecasted precisely. The investment environment is usually fuzzy and uncertain. To handle these imprecise data, this paper discusses a fuzzy multi-period portfolio optimization problem where the returns, risk, and liquidity of securities are represented by interval variables. By taking the return, risk, liquidity and diversification degree of portfolio into consideration, an interval multi-period portfolio selection optimization model is proposed with the objective of maximizing the terminal wealth under the constraints of the return, risk and diversification degree of portfolio at each period. In the proposed model, a proportion entropy is employed to measure the diversification degree of portfolio. Using the fuzzy decision-making theory and multi-objective programming approach, the proposed model is transformed into a crisp nonlinear programming. Then, we design an improved particle swarm optimization algorithm for solution. Finally, a numerical example is given to illustrate the application of our model and demonstrate the effectiveness of the designed algorithm.     

Multi-agent knowledge integration mechanism using particle swarm optimization

Unstructured group decision-making is burdened with several central difficulties: unifying the knowledge of multiple experts in an unbiased manner and computational inefficiencies. In addition, a proper means of storing such unified knowledge for later use has not yet been established. Storage difficulties stem from of the integration of the logic underlying multiple experts' decision-making processes and the structured quantification of the impact of each opinion on the final product. To address these difficulties, this paper proposes a novel approach called the multiple agent-based knowledge integration mechanism (MAKIM), in which a fuzzy cognitive map (FCM) is used as a knowledge representation and storage vehicle. In this approach, we use particle swarm optimization (PSO) to adjust causal relationships and causality coefficients from the perspective of global optimization. Once an optimized FCM is constructed an agent based model (ABM) is applied to the inference of the FCM to solve real world problem. The final aggregate knowledge is stored in FCM form and is used to produce proper inference results for other target problems. To test the validity of our approach, we applied MAKIM to a real-world group decision-making problem, an IT project risk assessment, and found MAKIM to be statistically robust.     

Large newsvendor games

We consider a game, called newsvendor game, where several retailers, who face a random demand, can pool their resources and build a centralized inventory that stocks a single item on their behalf. Profits have to be allocated in a way that is advantageous to all the retailers. A game in characteristic form is obtained by assigning to each coalition its optimal expected profit. We consider newsvendor games with possibly an infinite number of newsvendors. We prove in great generality results about balancedness of the game, and we show that in a game with a continuum of players, under a nonatomic condition on the demand, the core is a singleton. For a particular class of demands we show how the core shrinks to a singleton when the number of players increases.     

STATE-DEPENDENT PREFERENCES AND FUTURES HEDGING: THE EFFECTS OF BASIS RISK

Abstract. This note incorporates basis risk into the futures hedging decision-making problem when the hedger has a state-dependent preference. It is shown that, in an unbiased futures market, a partial hedge is optimal when the marginal utilities in different states are moderately close to each other. Conditions for a Texas hedge or an overhedge are provided. Finally, it is demonstrated that basis risk always reduces the futures trading volume.     

财政赤字的通货膨胀风险——理论诠释与中国的实证分析

财政赤字与通货膨胀的关系一直是理论界与决策部门密切关注的问题。文章在构建财政赤字与通货膨胀联系机制的理论框架基础上,结合两者在我国宏观经济运行中的客观运行轨迹,对我国财政赤字的通货膨胀风险进行了实证分析。实证结果表明,虽然我国财政赤字在不同的融资方式下均具有一定的货币扩张效应,但由于财政赤字的规模仍然在适度的范围内,财政赤字所引起的货币供给量增加幅度还不足以导致通货膨胀发生,我国财政赤字并不是通货膨胀产生的主要原因。     

RETURNS SYSTEM WITH REBATES*

We consider a variant of the newsvendor problem. Atomistic retailers each buy merchandise from a monopoly supplier for resale at a market‐determined common retail price that depends upon the total industry order quantity and upon a stochastic demand. After the orders are filled, the supplier learns the realization of demand but the retailers do not. We show that, in this setting, a returns system with rebates (with previously set buy‐back price for returns and ex post payments from the supplier to each retailer per unit actually sold) implements the optimal production and sales strategy, attaining maximum expected profit in the channel.     

基于物流金融模式的中小型企业融资风险评价研究

物流金融是解决中小型企业融资难问题的一种有效模式。针对其目前风险研究缺乏定量评价的问题,本文将多层次模糊综合评价法引入模型,构建了一个基于三方经营主体、定量与定性指标相结合的风险评价模型。最后利用此模型进行了实例分析,结果验证该模型具有很强的实用性和科学性,可为银行等提供有益的决策参考。     

Designing knowledge chain networks in China — A proposal for a risk management system using linguistic decision making

Designing Knowledge Supply Networks (KSN) with universities and research institutes has become a key source of technological innovations in Mainland China. In order to explore the key design principles, we first present typologies within KSN and explain the factors that can push, guide, or support the innovation process in such a network. Second, we identify and classify the particular risks that prevail when KSN are designed in an emerging region. To assess these risks, we next propose an advanced method that takes into consideration typical problems in group decision-making processes by applying linguistic operators derived from the field of decision theory and fuzzy-sets theory. The risk evaluation method is illustrated with a case study. Fourth, we offer advice on the mitigation of risks in KSN. Finally, we provide insights into the implementation of the risk evaluation method and its automation using Stakeholder Information Systems.     

基于价值函数的行为风险投资组合模型研究

从人的有限理性出发,强调风险投资者的实际心理感受对风险投资决策的影响,针对投资者对同等数量的损失比收益更加敏感的心理特征,运用价值函数将投资者的这种心理上的损失和收益引入风险投资决策中,同时用下偏矩来度量组合的风险,认为下偏矩更能反映投资者关心损失程度是否在自己能力承受范围内甚于关心损失概率的心理特征。在此基础上,建立了基于价值函数的单心理账户和多心理账户行为风险投资组合模型。