模糊多属性决策的三种结构元方法

将结构元理论引入到模糊多属性决策中,按照经典多属性决策的乐观型准则、悲观型准则和乐观-悲观结合型准则,对应地建立了基于模糊结构元理论的模糊乐观型、模糊悲观型、模糊乐观-悲观结合型决策方法。借助一个实例,本文运用这三种算法进行了决策,得出了和传统决策算法一致的结论。本文提出的算法不仅易于理解,而且计算的速度也远比传统算法要快,对于进一步研究模糊多属性决策问题有很好的参考作用。     

Learning and transfer in dynamic decision environments

An important aspect of learning is the ability to transfer knowledge to new contexts. However, in dynamic decision tasks, such as bargaining, firefighting, and process control, where decision makers must make repeated decisions under time pressure and outcome feedback may relate to any of a number of decisions, such transfer has proven elusive. This paper proposes a two-stage connectionist model which hypothesizes that decision makers learn to identify categories of evidence requiring similar decisions as they perform in dynamic environments. The model suggests conditions under which decision makers will be able to use this ability to help them in novel situations. These predictions are compared against those of a one-stage decision model that does not learn evidence categories, as is common in many current theories of repeated decision making. Both models' predictions are then tested against the performance of decision makers in an Internet bargaining task. Both models correctly predict aspects of decision makers' learning under different interventions. The two-stage model provides closer fits to decision maker performance in a new, related bargaining task and accounts for important features of higher-performing decision makers' learning. Although frequently omitted in recent accounts of repeated decision making, the processes of evidence category formation described by the two-stage model appear critical in understanding the extent to which decision makers learn from feedback in dynamic tasks. Faison (Bud) Gibson is an Assistant Professor at College of Business, Eastern Michigan University. He has extensive experience developing and empirically testing models of decision behavior in dynamic decision environments.     

基于结构元理论及信息熵的模糊多属性决策方法

主要目的是讨论当权重完全未知时的模糊多属性决策方法,其中运用了结构元理论和信息熵方法.首先,简单地介绍了这两种方法的基本原理.然后,提出了基于这两种方法的决策模型,给出了模糊权重函数的求解公式.最后,把该方法应用于考核、评估干部的问题.     

具有模糊数的模糊多目标群体决策优选模型与方法

多目标群体决策问题是运筹学的一个重要研究领域，目前已经提出了一些有效的决策方法。但对目标值和权重均为模糊数的模糊多目标群体决策问题却研究不多，本对此类模糊多目标群体决策问题进行了探讨，利用相对正理想方案与相对负理想方案概念定义了相对差异距离，进而建立了模糊多目标群体决策优选模型与方法，并通过战役决心方案的评价说明了该方法是可行、有效的，可作为军事决策与决策支持系统的备选方法。     

Extinction and blow-up phenomena in a non-linear gender structured population model

In this article we consider a gender structured model in population dynamics. We assume that the fertility rate depends upon the weighted population of males instead of total population of males. The proportion of males in the population is determined by fixed environmental or social conditions. Here we prove an existence and uniqueness result for a non-trivial steady state. If the initial age distribution is uniformly below the non-trivial steady state then we show that the total population goes extinct in infinite time. On the other hand, if we take the initial age distribution to be uniformly above the steady state then the total population blows up exponentially with time.     

A multicriteria approach for rating the credit risk of financial institutions

Within the new bank regulatory context, the assessment of the credit risk of financial institutions is an important issue for supervising authorities and investors. This study explores the possibility of a developing risk assessment model for financial institutions using a multicriteria classification method. The analysis is based on publicly available financial data for UK firms. The results indicate that the proposed multicriteria methodology provides promising results compared to well known statistical methods.     

Modelling the spread of bacterial disease: effect of service providers from an environmentally degraded region

In this paper, an SIS model for bacterial infectious diseases, like tuberculosis, typhoid, etc., caused by direct contact of susceptibles with infectives as well as by bacteria is proposed and analyzed. Here the demography of the human population is constant immigration and the cumulative rate of the environmental discharges is a function of total human population. Further this model is extended to the model for socially structured population (rich and poor) where poor people work as service provider in the houses of rich people but do not settle in the habitat of rich people. It is assumed that bacteria population does not survive in the clean environment of rich people and only affects the population in the degraded environment of the poor class. The stability of the equilibria is studied by using the theory of differential equation and computer simulation. It is concluded that the spread of the infectious disease increases when the growth of bacteria caused by conducive environmental discharge due to human sources increases. Also the spread of the infectious disease in rich class increases due to the interaction with service providers, who are living in relatively poor environmental condition, suggesting the need to keep our environment clean all around.     

On age-structured SIS epidemic model for time dependent population

1.IntroductionandPreliminaryAgestructureinepidemicmodelshasbeenconsideredbymanyauthors,becauseoftherecoghtionthattransmissiondynamicsofcertaindiseasescouldnotbecorrectlydescribedbythetraditionalepidemicmodelswithnoagedependence.Especially,Busenbergetal.II'2]giveacompleteanalysisofafairlygeneralSISmodelwithagestructureandasteady-statetotalpopulation,showingtheekistenceofathresholdforendemicstates.In[tis],theyassumethatthepopulationhasreacheditssteadystate.Althoughitisnotilladeqilatetoassumet…     

时序多指标决策的灰色关联分析法

本文对带有时间顺序的混合型多指标决策，运用灰色关联理论，建立了一种新的灰色关联决策模型，从而为时序多指标决策问题提供了又一科学，合理的决策方法。     

基于前景理论的三角犹豫模糊多属性决策方法

针对属性权重信息完全未知,属性值为三角犹豫模糊元的多属性决策问题,提出一种基于前景理论和模糊结构元的决策分析方法。首先,基于模糊结构元理论,定义三角犹豫模糊元的结构元形式和海明距离公式,并通过求解属性间距离离差最大化的优化模型确定权重。其次,依据前景理论,分别以正负理想点作为决策参照点,构建收益矩阵和损失矩阵。在此基础上,应用TOPSIS方法计算各备选方案的相对贴近度,并依据相对贴近度的大小实现备选方案排序。最后,通过算例验证方法是有效和可行的。     

Newsvendor models for innovative products with one-shot decision theory

In this paper, newsvendor problems for innovative products are analyzed. Because the product is new, no relevant historical data is available for statistical demand analysis. Instead of using the probability distribution, the possibility distribution is utilized to characterize the uncertainty of the demand. We consider products whose life cycles are expected to be smaller than the procurement lead times. Determining optimal order quantities of such products is a typical one-shot decision problem for a retailer. Therefore, newsvendor models for innovative products are proposed based on the one-shot decision theory (OSDT). The main contributions of this research are as follows: the general solutions of active, passive, apprehensive and daring focus points and optimal alternatives are proposed and the existence theorem is established in the one-shot decision theory; a simple and effective approach for identifying the possibility distribution is developed; newsvendor models with four types of focus points are built; managerial insights into the behaviors of different types of retailers are gained by the theoretical analysis; the proposed models are scenario-based decision models which provide a fundamental alternative to analyze newsvendor problems for innovative products.     

依据主、客观权重集成最终权重的一种方法

本文根据已掌握的主、客观信息，利用最优化技术构造既反映主观信息，又反映客观信息的确定属性权重的最优化模型，通过求解该优化模型得出各属性的最终权重．     

种群生理结构模型解的性质

考虑具有生长率的种群生理结构动力学模型,讨论了系统解的渐近性质,当系统具有多平衡解时,指出各平衡解的稳定性。     

Is politics power or policy oriented? A comparative analysis of dynamic access models in policy networks*

We will show that these base models and some intermediate ones result in fundamentally different network structures and predicted outcomes. Moreover, we will show that the policy driven models do fundamentally better than the power driven models.

In policy networks actors use access relations to influence preferences of other actors. Establishment and shifts of access relations and their consequences for outcomes of decisions are the main focal points in this paper. Unlike most policy network studies, we therefore do not take the network and its relations as given and constant. Instead we device computer simulation models to account for the dynamics in policy networks. We compare different models and investigate the resulting network structures and predicted outcomes of decisions. The choice among the alternative models is made by their correspondence with empirical network structures and actual outcomes of decisions.

In our models, we assume that all relevant actors aim at policy outcomes as close as possible to their own preferences. Policy outcomes are determined by the preferences of the final decision makers at the moment of the vote. In general, only a small fraction of the actors takes part in the final vote. Most actors have therefore to rely on access relations for directly or indirectly shaping the preferences of the final decision makers. For this purpose actors make access requests to other actors. An access relation is assumed to be established if such a request is accepted by the other actor.

Access relations require time and resources. Actors are therefore assumed to be restricted in the number of access requests they can make and the number of requests they can accept Moreover, due to incomplete information and simultaneous actions by other actors, actors have to make simplifying assumptions in the selection of their “best” requests and learn by experience.

We device two base models that correspond to two basic views on the nature of political processes. In the first view politics is seen as power driven. Corresponding to this view, actors aim at access relations with the most powerful actors in the field. They estimate their likelihood of success by comparing their own resources with those of the target actors. Power also determines the order in which actors accept requests. In the second view, policy matters and actors roughly estimate the effects access relations might have on the outcome of decisions. Actors select requests to “bolster” their own preference as much as possible.     

城镇化进程中洛阳市人口发展的数学建模探讨

针对城镇化进程中洛阳市的人口发展规律,建立了人口发展的一元线性回归模型、指数增长模型以及阻滞增长的Logistic模型来预测洛阳市人口的发展,并与ARIMA模型进行了对比,为城镇化进程中人口发展趋势提供参考,为政策的制定者提供理论指导和决策参考。