组合评价模型在河南省主要城市综合经济实力评价中的应用

组合评价模型通过组合多个单一评价模型的评价结果,有效弥补单一方法的不足,提高评价的全面性和科学性.首先利用河南省2010年的相关数据,分别采用综合指数法、加权平均法、主成分分析法和因子分析法,对河南省的18个主要地区的综合经济实力进行了评价和排序;其次,建立基于模糊Borda法的组合评价模型,应用该模型对河南省的18个主要地区的综合经济实力进行了重新评价和排序,得到了更为可行的评价结果.     

基于集对分析的组合评价模型及其应用

组合评价是目前处理单一评价方法的不一致性、提高评价结果的可靠性和合理性的有效途径,现有的组合评价方法的主要不足是对这些单一评价法的评价排序值之间的一致性信息利用尚不够充分.提出用集对分析方法的联系度从同、异、反三方面定量描述这些一致性信息、并用于构造模糊互补判断矩阵来确定各单一评价法的组合权重的新模型(CEM-SPA).CEM-SPA的应用结果表明:CEM-SPA的组合评价结果比单一评价法更具有可靠性和合理性,与各单一评价法的相容性均很高;CEM-SPA利用各单一评价法的相容性测度确定各单一评价法的权重,利用各单一评价法的信息比常用的平均值法更充分因而显得更为合理;CEM-SPA在基于评价排序值的系统组合评价中具有推广应用价值.     

基于方法集的棕地再开发项目组合评价研究

棕地再开发项目综合评价具有重要的理论意义实践意义.为了科学、合理地对棕地再开发项目进行评价,提出了一种基于方法集的组合评价模型.首先,分别应用灰色关联评价、模糊综合评价、TOPSIS和主成分评价分别对备选方案进行单一评价;然后,使用KENDALL-W协和系数检验对单一评价的排序结果进行统计一致性检验,并以满足统计一致性的评价方法构成方法集;其次,分别使用平均值法、Borda法、Copeland法对单一评价的排序结果进行组合评价,并使用循环组合的方法保证组合评价结果的完全一致性;最后,应用该模型对某市棕地再开发项目进行组合评价,评价结果验证了模型的有效性.     

基于方案综合评价值和效用值偏差的多属性决策方法

研究了属性权重未知、方案偏好为效用值的多属性决策问题,提出了一种多属性决策模型.首先,分析了部分文献中利用方案属性值与效用值的偏差建模求出属性权重的不合理性,以及根据方案综合评价值与效用值的偏差建模得到属性权重的合理性.然后,通过最小化方案综合评价值与效用值的偏差,建立了一个规划模型,计算出属性权重,进而利用方案综合评价值实现方案的排序择优.最后,通过一个实例说明了方法的可行性.     

基于组合评价的长三角城市基础设施投资绩效研究

城市基础设施投资绩效的合理评价是进行科学投资决策的重要依据。为了对长三角25个城市基础设施投资绩效进行客观、合理的评价,建立了基础设施投资绩效评价指标体系,选取2009年截面数据采用组合评价法进行综合评价。该方法首先使用超效率DEA、熵权TOPSIS、因子分析三种方法得出各自结果下的排名,在验证了各评价方法具有一致性的前提下采用模糊Borda综合评价法得出各城市的最终排名。组合评价方法弥补了单一方法的不足,有助于得到更客观合理的评价结果,为有关城市和部门把握基础设施投资绩效和未来决策提供参考。     

一种不完全信息的多属性决策模型及其灵敏度分析

针对具有区间信任结构的不完全信息的多属性决策问题,建立了一组集结各属性区间信任度的优化模型,得到每个方案属于各个评价等级的总体信任度.在这一优化模型的基础上,建立了计算期望效用值的约束优化模型,通过求解该优化问题,得到各方案的期望效用值,用期望效用值对决策方案进行排序.分析了期望效用值对属性权系数的灵敏度,提出了一种方案排序结果对决策参数的灵敏度分析方法.最后,用算例验证了模型的有效性.     

基于组合赋权和灰色关联投影法的区域能源供应系统评价研究

通过分析区域能源供应系统综合性能评价影响因素,设计系统评价指标体系,运用层次分析法(AHP)和熵权法结合的组合赋权法确定指标权重,构建加权灰色关联决策矩阵,最终提出了一种基于组合赋权和灰色关联投影法的区域能源供应系统方案优选方法.运用灰色关联投影值对备选方案进行优劣排序,案例分析表明该模型具有程序化、科学实用、便于操作等特点,具有推广和应用价值.     

考虑决策者给出部分属性期望的风险型多属性决策方法

针对决策者给出部分属性期望的风险型多属性决策问题,提出了一种决策分析方法。在该方法中,首先,依据决策者在各自然状态下给出的属性期望信息,将原始决策问题转化为没有属性期望和具有属性期望的两个独立的风险型多属性决策问题;然后,针对没有属性期望的风险型多属性决策问题,依据期望效用理论,计算各属性下属性值所对应的效用值,进而得到每个方案的综合效用值;进一步地,针对具有属性期望的风险型多属性决策问题,依据累积前景理论,将决策者给出的属性期望视为属性的参照点,进而计算各属性值的前景价值及决策权重函数值并计算每个方案的综合累积前景值;在此基础上,计算得到每个方案的总体效用值,并依据总体效用值的大小对所有方案进行排序。最后,通过一个算例说明了该方法的可行性和有效性。     

一种具有不同形式效用值的群决策方法

研究了具有实数值、区间数和语言短语等三种形式效用值信息的群决策问题．首先给出了具有不同形式效用值的群决策问题的描述；然后给出了具有三种形式效用值的群决策方法的计算步骤．在该方法中，将不同形式的效用值均转化为区间数形式的效用值，通过加权法则得到每个方案的区间数群体综合效用值，并依据群体综合效用值进行方案的排序．最后通过给出一个算例说明了本给出的方法．     

基于虚拟最劣解TOPSIS和灰关联度的动态评价方法

为了比较多个系统在不同时刻的发展水平和某一段时间的动态累积水平,需要进行动态评价.针对传统TOPSIS和灰关联度法优缺点,提出新贴近度,同时反映了方案与理想方案和虚拟最劣解之间的位置关系以及方案和理想方案数据曲线的相似性差异.引入虚拟最劣解对传统TOPSIS进行改进,将二维数据加入时序数据扩展为三维数据,提出基于虚拟最劣解TOPSIS和灰关联度的动态评价方法,该方法既可以得到反映各评价对象指标值差异程度的评价值及排序结果,也可以得到各评价对象增长程度的评价值及排序结果,还可以得到同时考虑各评价对象指标值差异程度和增长程度的综合评价值.根据决策者对位置和形状的偏好程度以及存量和增量偏好程度不同,对相应参数取不同值.既可以得到各评价对象各时刻的综合评价值及排序,也可以得到各评价对象在某个时间段内总体的评价值和排序结果.最后将该方法应用于"十二五"期间区域协同创新能力评价,通过实例验证该方法实际应用上的有效性.     

医院管理综合评价方法的组合与优化

针对医院管理中单一综合评价方法的不足,基于评价结果的一致性和评价方法的兼容性对四种评价方法进行比较、组合和优化,提出一种改进的平均值组合方法.使其评价结果更合理,兼容性更高.     

Homogeneity Rank and Atoms of Actions

We introduce two related concepts for smooth actions of compact Lie groups:The homogeneity rank is a simple numerical invariant of the action.As one of our results we determine the precise range of this invariantfor isometric actions on compact Riemannian manifolds with positivesectional curvature and exhibit special properties of the actionswith maximal homogeneity rank.Atoms are special components of fixed point sets. They inherit actionswith the same cohomogenity and homogeneity rank as the original action,but with trivial principal isotropy group. Other properties of the originalaction like polarity are reflected in the atoms.We determine the atoms in some interesting concrete cases.Not only for this purpose we give a detailed treatise on the structureof fixed point sets, in particular in cohomogeneity one manifolds.     

Evolutionary methods for unsupervised feature selection using Sammon’s stress function

In this paper, four methods are proposed for feature selection in an unsupervised manner by using genetic algorithms. The proposed methods do not use the class label information but select a set of features using a task independent criterion that can preserve the geometric structure (topology) of the original data in the reduced feature space. One of the components of the fitness function is Sammon’s stress function which tries to preserve the topology of the high dimensional data when reduced into the lower dimensional one. In this context, in addition to using a fitness criterion, we also explore the utility of unfitness criterion to select chromosomes for genetic operations. This ensures higher diversity in the population and helps unfit chromosomes to become more fit. We use four different ways for evaluation of the quality of the features selected: Sammon error, correlation between the inter-point distances in the two spaces, a measure of preservation of cluster structure found in the original and reduced spaces and a classifier performance. The proposed methods are tested on six real data sets with dimensionality varying between 9 and 60. The selected features are found to be excellent in terms of preservation topology (inter-point geometry), cluster structure and classifier performance. We do not compare our methods with other methods because, unlike other methods, using four different ways we check the quality of the selected features by finding how well the selected features preserve the “structure” of the original data.     

An inexact parallel splitting augmented Lagrangian method for large system of linear equations

Parallel iterative methods are powerful in solving large systems of linear equations (LEs). The existing parallel computing research results focus mainly on sparse systems or others with particular structure. Most are based on parallel implementation of the classical relaxation methods such as Gauss-Seidel, SOR, and AOR methods which can be efficiently carried out on multiprocessor system. In this paper, we propose a novel parallel splitting operator method in which we divide the coefficient matrix into two or three parts. Then we convert the original problem (LEs) into a monotone (linear) variational inequality problem (VI) with separable structure. Finally, an inexact parallel splitting augmented Lagrangian method is proposed to solve the variational inequality problem (VI). To avoid dealing with the matrix inverse operator, we introduce proper inexact terms in subproblems such that the complexity of each iteration of the proposed method is O(n²). In addition, the proposed method does not require any special structure of system of LEs under consideration. Convergence of the proposed methods in dealing with two and three separable operators respectively, is proved. Numerical computations are provided to show the applicability and robustness of the proposed methods.     

Weakly Hyperbolic Actions of Kazhdan Groups on Tori

We study the ergodic and rigidity properties of weakly hyperbolic actions. First, we establish ergodicity for C² volume preserving weakly hyperbolic group actions on closed manifolds. For the integral action generated by a single Anosov diffeomorphism this theorem is classical and originally due to Anosov. Motivated by the Franks/Manning classification of Anosov diffeomorphisms on tori, we restrict our attention to weakly hyperbolic actions on the torus. When the acting group is a lattice subgroup of a semisimple Lie group with no compact factors and all (almost) simple factors of real rank at least two, we show that weak hyperbolicity in the original action implies weak hyperbolicity for the induced action on the fundamental group. As a corollary, we obtain that any such action on the torus is continuously semiconjugate to the affine action coming from the fundamental group via a map unique in the homotopy class of the identity. Under the additional assumption that some partially hyperbolic group element has quasi-isometrically embedded lifts of unstable leaves to the universal cover, we obtain a conjugacy, resulting in a continuous classification for these actions. Partially funded by VIGRE grant DMS-9977371 Received: January 2005 Revision: August 2005 Accepted: September 2005     

A scoring mechanism for the rank aggregation of network robustness

To date, a number of metrics have been proposed to quantify inherent robustness of network topology against failures. However, each single metric usually only offers a limited view of network vulnerability to different types of random failures and targeted attacks. When applied to certain network configurations, different metrics rank network topology robustness in different orders which is rather inconsistent, and no single metric fully characterizes network robustness against different modes of failure. To overcome such inconsistency, this work proposes a multi-metric approach as the basis of evaluating aggregate ranking of network topology robustness. This is based on simultaneous utilization of a minimal set of distinct robustness metrics that are standardized so to give way to a direct comparison of vulnerability across networks with different sizes and configurations, hence leading to an initial scoring of inherent topology robustness. Subsequently, based on the inputs of initial scoring a rank aggregation method is employed to allocate an overall ranking of robustness to each network topology. A discussion is presented in support of the presented multi-metric approach and its applications to more realistically assess and rank network topology robustness.     

Rank reversals in multi-criteria decision analysis with statistical modelling of ratio-scale pairwise comparisons

In multi-criteria decision analysis, the overall performance of decision alternatives is evaluated with respect to several, generally conflicting decision criteria. One approach to perform the multi-criteria decision analysis is to use ratio-scale pairwise comparisons concerning the performance of decision alternatives and the importance of decision criteria. In this approach, a classical problem has been the phenomenon of rank reversals. In particular, when a new decision alternative is added to a decision problem, and while the assessments concerning the original decision alternatives remain unchanged, the new alternative may cause rank reversals between the utility estimates of the original decision alternatives. This paper studies the connections between rank reversals and the potential inconsistency of the utility assessments in the case of ratio-scale pairwise comparisons data. The analysis was carried out by recently developed statistical modelling techniques so that the inconsistency of the assessments was measured according to statistical estimation theory. Several type of decision problems were analysed and the results showed that rank reversals caused by inconsistency are natural and acceptable. On the other hand, rank reversals caused by the traditional arithmetic-mean aggregation rule are not in line with the ratio-scale measurement of utilities, whereas geometric-mean aggregation does not cause undesired rank reversals.     

组合评价模型在港口物流综合服务能力评价中的应用

为了对港口物流综合服务能力进行科学评价,提出了基于组合评价方法的港口物流服务能力评价模型,并对我国15个港口的物流综合服务能力进行实证分析说明模型的有效性.首先分别采用5种评价方法进行评价,然后使用KendallW系数检验各方法评价结果的一致性,再运用4种组合评价模型进行组合评价,采用Spearman等级系数进行事后检验并得到最终结果.方法可克服单一评价方法的不足,为港口物流服务能力评价提供新的思路.     

基于可拓和组合赋权的矿井通风系统优化评价

矿井通风系统具有随机性、模糊性和不确定性等特征,一般单一的赋权评价法难以对其进行准确的优化评价.采用模糊层次分析法和熵权法的组合赋权法不仅可以提升对目标评价的准确性还能避免单一赋权的偶然性和局限性,结合可拓学的优度评价法,依据优度排序,得到最优方案.事实证明,基于组合赋权的可拓评价模型较其他评价方法更为客观,评价结果更加符合实际,可为解决类似优化方案问题提供一种新思路和方法.     

Fuzzy measures of supplier evaluation under lean concepts

Supplier evaluation is a multiple attribute decision-making (MADM) problem involving a mixture of qualitative and quantitative attributes. Some mathematical programming techniques have difficulty in dealing with the qualitative attributes that are not easy to measure but very important in supplier evaluation. Fuzzy set theory is useful whenever variables defining a complex and vague system can neither be quantitatively defined nor assigned very precise measures, but are described by linguistic values. This paper presents a procedure for supplier evaluation by incorporating fuzzy set theory into the evaluation process to handle the qualitative attributes in the problem. A mathematical ranking method is used to convert the qualitative attributes into crisp scores. All the quantitative and qualitative performance measures are normalized and then using the proposed model, data are integrated into a single score to rank suppliers. The model application is demonstrated through two previously reported data sets under lean philosophy.