基于模糊综合评判方法的DEA模型

利用数据包络分析和多目标规划的有关理论,对模糊综合评判方法进行进一步探讨,给出一个建立在模糊综合评判过程基础上的DEA模型,该方法不仅能够增强模糊综合评判结果的客观性,更重要的是它可以找出模糊综合评判中较差单元无效的原因,并能为较差单元的改进提供许多有用的信息。     

区域经济系统的ARX参数模型估计

利用系统辨识的方法,对非线性系统进行输入、输出分析,利用模糊评判的输入、输出数据,从多个非线性模型中,确定出一个能够反映区域经济系统特征的模型,从而形成了一种建构在模糊评判基础上系统辨识新思路.     

基于模糊综合评判的预警机作战效能评估

根据预警机的功能结构关系,建立了预警机的效能评估指标体系;针对预警机作战效能评估多指标和不确定性的特点,结合模糊综合评判法建立了预警机作战效能评估的多层模糊综合评判模型;通过实例验证了模型的正确性和有效性.     

消费者转基因食品人体健康风险认知模糊多属性综合评判

研究了消费者转基因食品人体健康风险认知模糊多属性评判模型.首先建立评价指标体系,其次根据问卷调查数据按频率分布转化成隶属度得到模糊关系矩阵,利用AHP和熵权法得到权向量,利用加权评价算子得到评判结果,最后对结果进行了讨论并提出相应的政策建议.     

基于灰色关联分析的财产保险公司偿付能力的模糊综合评判

为解决财产保险公司的偿付能力的评价问题,建立了基于灰色关联分析的模糊综合评判模型.选取了2003-2005年我国8家财产保险公司的相关数据,用灰色关联分析中的点关联系数求解隶属度得出评判矩阵,用范数灰关联度法确定因素集中各因素的权重,从而对其偿付能力进行模糊综合评判,得出各公司的偿付能力所属的类别.并对评语集中各评语赋予适当的权重,对所研究的8家财产保险公司依据其偿付能力的情况进行了排序.     

基于模糊综合评判的炮阵地评估模型研究

通过对影响选择炮兵群阵地的各项因素进行量化分析,利用模糊综合评判的有关理论,建立炮阵地的模糊评判模型,并举例予以验证.     

不确定环境下基于交叉评价的模糊综合评价方法

由于环境的不确定性,多属性决策中客观数据和主观因素并存,决策者很难做出精准的评判.借鉴DEA交叉评价的思想,将量化数据用交叉评价方法进行处理,得出平均交叉效率值作为模糊综合评价的指标进行二次评价.建立了不确定环境下基于交叉评价的模糊综合评价模型,并通过评价实例验证了模型的客观、全面性.     

模糊综合评判在高校排课系统评价中的应用

模糊综合评判是一种应用广泛的模糊数学方法,是在综合考虑和整体平衡中顾及各种因素全面进行评判的科学方法,可广泛应用在各类人员、工作、产品等等客体的综合评判工作中.本文主要采用模糊数学理论对我院排课系统进行综合评价,经确定评判因素集、权重、等级评语向量和评价矩阵等,从而得到了三级模糊综合评判模型.结果表明该模型用于排课系统评估,客观公正,可信度高.     

模糊优选模型及其应用

模糊综合评判在经济中应用十分广泛,然而由于传统的模糊综合评判模型依赖于隶属函数的确定,并往往带有较强的“主观任意性”,且不同的函数组合对评判结果的影响较大,故评判结果有时难以令人信服.本文对适度型指标的相对隶属函数———优属度的计算提出了具体方法,使模糊优选模型更具有实用性.这一新的模糊优选途径,具有理论严谨,概念明确,计算简便实用的特点,是解决大系统模糊优选问题的有效方法.文中还结合港口类上市公司绩效的综合评价进行了实证分析,获得了理想的效果.     

关于AHP中群体决策逆判问题的研究

用统计分析法及模糊分析及对AHP中评判专家的评判（即逆判）问题进行了研究，对评判专家的评判水平给出了排序及分类的方法，并通过示例验证了该方法的可行性。     

关于综合 DEA 模型中的 DEA 有效决策单元集合的几个恒等式

DEA 模型(C~2R 模型,C~2GS~2模型,C~2W 模型和 C~2WH 模型等)是用来评价决策单元之间的相对有效性的.本文将给出关于具有更一般形式的综合 DEA 模型中的 DEA 有效决策单元集合的几个恒等式.这些等式表明在评价相对有效性时,可以将决策单元按照实际情况进行分组,先评价组内决策单元之间的相对有效性,再利用得到的信息进行不同组之间的有效决策单元的效率评价,如此等等.这种分组逐一进行评价的     

Finding market structure by sales count dynamics—Multivariate structural time series models with hierarchical structure for count data—

In this paper, we propose a multivariate time series model for sales count data. Based on the fact that setting an independent Poisson distribution to each brand’s sales produces the Poisson distribution for their total number, characterized as market sales, and then, conditional on market sales, the brand sales follow a multinomial distribution, we first extend this Poisson–multinomial modeling to a dynamic model in terms of a generalized linear model. We further extend the model to contain nesting hierarchical structures in order to apply it to find the market structure in the field of marketing. As an application using point of sales time series in a store, we compare several possible hypotheses on market structure and choose the most plausible structure by using several model selection criteria, including in-sample fit, out-of-sample forecasting errors, and information criterion.     

Delta hedging strategies comparison

In this paper we implement dynamic delta hedging strategies based on several option pricing models. We analyze different subordinated option pricing models and we examine delta hedging costs using ex-post daily prices of S&P 500. Furthermore, we compare the performance of each subordinated model with the Black–Scholes model.     

Dynamic mortality factor model with conditional heteroskedasticity

In most methods for modeling mortality rates, the idiosyncratic shocks are assumed to be homoskedastic. This study investigates the conditional heteroskedasticity of mortality in terms of statistical time series. We start from testing the conditional heteroskedasticity of the period effect in the naïve Lee-Carter model for some mortality data. Then we introduce the Generalized Dynamic Factor method and the multivariate BEKK GARCH model to describe mortality dynamics and the conditional heteroskedasticity of mortality. After specifying the number of static factors and dynamic factors by several variants of information criterion, we compare our model with other two models, namely, the Lee-Carter model and the state space model. Based on several error-based measures of performance, our results indicate that if the number of static factors and dynamic factors is properly determined, the method proposed dominates other methods. Finally, we use our method combined with Kalman filter to forecast the mortality rates of Iceland and period life expectancies of Denmark, Finland, Italy and Netherlands.     

Design of a wind farm collection network when several cable types are available

In this article we consider a real-world problem submitted to us by the Hatch company. This problem consists of designing a collection network for a wind farm, assuming that the locations of the turbines and the potential cables are known, several cable types are available, and the cost of the energy that dissipates through the cables is known. We propose a mixed integer quadratic programme to model the network design problem and then linearize the quadratic programme because the latter is too difficult to solve using a standard mathematical programming software. We describe several classes of inequalities that strengthen the resulting mixed integer linear programme. Finally we use real-world data supplied by Hatch to carry out computational experiments with several versions of our model.     

Asymptotic behavior of a stochastic virus dynamics model with intracellular delay and humoral immunity

In this paper, we formulate a stochastic virus dynamics model with intracellular delay and humoral immunity. By constructing some suitable Lyapunov functions, we show that the solution of stochastic model is going around each of the steady states of the corresponding deterministic model under some conditions. Then, numerical simulations are given to support the theoretical results. Finally, we propose several more effective way to control the spread of the virus by analyzing the sensitivity of the threshold of spread.     

A polynomial algorithm for the multicriteria cent-dian location problem

Given a network with several weights per node and several lengths per edge, we address the problem of locating a facility on the network such that the convex combinations of the center and median objective functions are minimized. Since we consider several weights and several lengths, various objective functions should be minimized, and hence we have to solve a multicriteria cent-dian location problem. A polynomial algorithm to characterize the efficient location point set on the network is developed. Furthermore, this model can generalize other problems such as the multicriteria center problem and the multicriteria median problem. Computing time results on random planar networks considering different combinations of weights and lengths are reported, which strengthen the polynomial complexity of the procedure.     

Robust supply chain network design with service level against disruptions and demand uncertainties: A real-life case

We have developed a stochastic mathematical formulation for designing a network of multi-product supply chains comprising several capacitated production facilities, distribution centres and retailers in markets under uncertainty. This model considers demand-side and supply-side uncertainties simultaneously, which makes it more realistic in comparison to models in the existing literature. In this model, we consider a discrete set as potential locations of distribution centres and retailing outlets and investigate the impact of strategic facility location decisions on the operational inventory and shipment decisions of the supply chain. We use a path-based formulation that helps us to consider supply-side uncertainties that are possible disruptions in manufacturers, distribution centres and their connecting links. The resultant model, which incorporates the cut-set concept in reliability theory and also the robust optimisation concept, is a mixed integer nonlinear problem. To solve the model to attain global optimality, we have created a transformation based on the piecewise linearisation method. Finally, we illustrate the model outputs and discuss the results through several numerical examples, including a real-life case study from the agri-food industry.     

变系数ARCH模型绝对值序列的强大数定律

本文提出一种新的模型: 变系数ARCH模型, 其中系数是时间变量的函数. 这与在不同的时间区间上拟和模型时系数是不同的这一事实是相符的. 所以这一模型更符合实际, 更合理. 由于系数是时间变量的函数, 所以这一模型有许多潜在的优点, 它更具有灵活性. 在本文中我们主要研究变系数ARCH模型绝对值序列的强大数定律.     

Pricing of Spread Options on a Bivariate Jump Market and Stability to Model Risk

Abstract

We study the pricing of spread options and we obtain a Margrabe-type formula for a bivariate jump-diffusion model. Moreover, we study the robustness of the price to model risk, in the sense that we consider two types of bivariate jump-diffusion models: one allowing for infinite activity small jumps and one not. In the second model, an adequate continuous component describes the small variation of prices. We illustrate our computations by several examples.