Orderings based on the banks set: Some new scoring methods for multicriteria decision making

This article introduces new methods for ranking alternatives in multicriteria decision making situations. Each is based on the normative position that the strength of an alternative is inversely related to the number of alternatives that could prevent it from being chosen. The scores discriminate among elements of the Banks set (Banks, Soc Choice Welfare, 1985, 1, 295–306). The new scoring methods are compared to traditional scoring methods and related to the amount of intransitivity (specifically, the size of the top‐cycle) of aggregated preference. The new scores are shown to measure important aspects of alternatives not captured by extant scoring methods and are illustrated in collective choice settings. © 2014 Wiley Periodicals, Inc. Complexity 20: 63–76, 2015     

Comparing influence theories in voting games under locally generated measures of dissatisfaction

The Isbell desirability relation (I), the Shapley?CShubik index (SS) and the Banzhaf?CColeman index (BC) are power theories that grasp the notion of individual influence in a yes?Cno voting rule. Also, a yes?Cno voting rule is often used as a tool for aggregating individual preferences over any given finite set of alternatives into a collective preference. In this second context, Diffo Lambo and Moulen (DM) have introduced a power relation which ranks the voters with respect to how ably they influence the collective preference. However, DM relies on the metric d that measures closeness between preference relations. Our concern in this work is: do I, SS, BC and DM agree when the same yes?Cno voting rule is the basis for collective decision making? We provide a concrete and intuitive class of metrics called locally generated (LG). We give a characterization of the LG metrics d for which I, SS, BC and DM agree on ranking the voters.     

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.     

Models of social contagion

This paper argues that social choice from among more than two feasible alternatives should not be based on social choice from two‐alternative subsets. It considers in some detail the case where one alternative ties or beats every other alternative on the basis of simple majorities, and raises the question of whether such an alternative should be chosen. A condition of ‘stochastic unanimity’, introduced in this context, is shown to be incompatible with the simple majority rule when it can apply. This new condition plus a consideration of ties leads into a brief discussion of the use of individual expected utility in social choice theory.     

Fuzzy hierarchical analysis

This paper extends hierarchical analysis to the case where the participants are allowed to employ fuzzy ratios in place of exact ratios. If a person considers alternative A more important than alternative B, then the ratio used might be approximately 3 to 1, or between 2 to 1, and 4 to 1, or at most 5 to 1. The pairwise comparison of the issues and the criteria in the hierarchy produce fuzzy positive reciprocal matrices. The geometric mean method is employed to calculate the fuzzy weights for each fuzzy matrix, and these are combined in the usual manner to determine the final fuzzy weights for the alternatives. The final fuzzy weights are used to rank the alternatives from highest to lowest. The highest ranking contains all the undominated issues. The procedure easily extends to the situation where many experts are utilized in the ranking process, or to the case of missing data. Two examples are presented showing the final fuzzy weights and the final ranking.     

Limited resoluteness and strategic voting: The case of linear sincere preference orderings

This note is concerned with the strategic manipulation of the aggregation procedures, which for every profile of individual preference orderings and every set of alternatives (presented for choice) specify a non-empty subset of alternatives. In the context of multi–valued aggregation procedures, the strategic behaviour of an individual crucially depends on the criterion of comparing different subsets of alternatives. It is shown that when the sincere (or true) preference orderings are restricted to be strict, the requirement of resoluteness in pairwise choice is the frontier between the manipulability and non-manipulability results in social choice as long as individuals adopt some versions of the sure-thing principle in comparing different subsets of alternatives.     

Scoring indices,top-truncated preferences,and splitting invariance

We present a new characterization of the class of weight-based scoring indices for ranking problems with top-truncated preferences. The main novel axiom is Splitting Invariance: if an alternative is split up into a number of distinct yet unranked alternatives, then the total score of these alternatives should increase by the score of the original alternative, and the scores of the other alternatives should not change.     

关于切丛和单位切球丛的度量的一个注记

本文在黎曼流形$(M,g)$的切丛$TM$ 上研究与参考文献[10]中平行的一类度量$G$以及相容的近复结构$J$.证明了切丛$TM$关于这些度量和相应的近复结构是局部共形近K\"{a}hler流形,并且把这些结构限制在单位切球丛上得到了切触度量结构的新例子.     

A quantitative Arrow theorem

Arrow’s Impossibility theorem states that any constitution which satisfies independence of irrelevant alternatives (IIA) and unanimity and is not a dictator has to be non-transitive. In this paper we study quantitative versions of Arrow theorem. Consider n voters who vote independently at random, each following the uniform distribution over the six rankings of three alternatives. Arrow’s theorem implies that any constitution which satisfies IIA and unanimity and is not a dictator has a probability of at least 6^?n for a non-transitive outcome. When n is large, 6^?n is a very small probability, and the question arises if for large number of voters it is possible to avoid paradoxes with probability close to 1. Here we give a negative answer to this question by proving that for every ${\epsilon > 0}$ , there exists a ${\delta = \delta(\epsilon) > 0}$ , which depends on ${\epsilon}$ only, such that for all n, and all constitutions on three alternatives, if the constitution satisfies:

• The IIA condition.
• For every pair of alternatives a, b, the probability that the constitution ranks a above b is at least ${\epsilon}$ .
• For every voter i, the probability that the social choice function agrees with a dictatorship on i at most ${1-\epsilon}$ .

Then the probability of a non-transitive outcome is at least δ. Our results generalize to any number k ≥ 3 of alternatives and to other distributions over the alternatives. We further derive a quantitative characterization of all social choice functions satisfying the IIA condition whose outcome is transitive with probability at least 1 ? δ. Our results provide a quantitative statement of Arrow theorem and its generalizations and strengthen results of Kalai and Keller who proved quantitative Arrow theorems for k?=?3 and for balanced constitutions only, i.e., for constitutions which satisfy for every pair of alternatives a, b, that the probability that the constitution ranks a above b is exactly 1/2. The main novel technical ingredient of our proof is the use of inverse-hypercontractivity to show that if the outcome is transitive with high probability then there are no two different voters who are pivotal with for two different pairwise preferences with non-negligible probability. Another important ingredient of the proof is the application of non-linear invariance to lower bound the probability of a paradox for constitutions where all voters have small probability for being pivotal.     

Causal analysis of futures sugar prices in Zhengzhou

In this paper, we are interested in investigating the causal relationships among futures sugar prices in the Zhengzhou futures exchange market (ZF), the spot sugar prices in Zhengzhou (ZS) and the futures sugar prices in New York futures exchange market (NF). A useful tool called Bayesian network is introduced to analyze the problem. Since there are only three variables in our Bayesian network, the algorithm is straightforward: we display all the 25 possible network structures and adopt certain scoring metrics to evaluate them. We applied five different scoring metrics in total. Firstly, for each metric, we obtained 24 scores, each calculated from one of the 24 possible structures i.e. a Directed Acyclic Graph (DAG). Then we eliminated the network structure which represents the independence of the three variables according to our prior knowledge concerning the futures sugar market. After that, the optimal network structure which implies the causal relationships was selected according to the corresponding scoring metric. Finally, after comparing the results from different scoring metrics, we obtained the relatively affirmative conclusion that ZS causes ZF from both the Bayesian Dirichlet (BD) metric, Bayesian Dirichlet-Akaike Information Criterion (BD-AIC) metric, Bayesian Dirichlet-Bayesian Information Criterion (BD-BIC) metric and Bayesian Information Criterion (BIC) metric. The conclusions that NF causes ZF and ZF causes ZS from the Akaike Information Criterion (AIC) metric and ZF causes ZS from the BIC metric were useful and significant to our investigation.     

Integrability Criterion of Geodesical Equivalence. Hierarchies

We prove that the Riemannian metrics g and (given in `general position") are geodesically equivalent if and only if some canonically given functions are pairwise commuting integrals of the geodesic flow of the metric g. This theorem is a multidimensional generalization of the well-known Dini theorem proved in the two-dimensional case. A hierarchy of completely integrable Riemannian metrics is assigned to any pair of geodesically equivalent Riemannian metrics. We show that the metrics of the standard ellipsoid and the Poisson sphere lie in such an hierarchy.     

Due Date-Based Metrics for Activity Importance in Stochastic Activity Networks

A metric pair for assessing the importance of activities in stochastic activity networks based on completing a project on time (or reaching other project milestones) is presented. The metric pair is recommended as a supplement to other metrics of activity importance that have been suggested for use with Monte Carlo simulation. The differences in behavior of the various metrics are analyzed to help understand the additional types of insights that would be available by including the new metrics in simulation-based analyses.     

数控车床可靠性分配中的单准则排序方法

数控车床可靠性分配模型是一个层次结构,可靠性分配的关键技术是确定结构底层指标关于顶层目标的重要度排序,其前提条件是单准则排序已知.AHP通过构造"两两比较"的"1~9"比例标度判断矩阵A_n为单准则排序提供了合理的数据条件;但是基于A_n一致性检验的特征根排序法因临界值的确定缺乏必要理论基础而受到质疑.改进AHP的FAHP因为没有摆脱"一致性检验"的干扰所以改进并不成功.为了建立与"一致性"无关的单准则排序方法定义具有可加性的评分标度概念,通过标度转换将比例标度判断矩阵A_n转化为评分标度判断矩阵B_n,利用评分标度的可加性在准则C下对n个比较对象排序.因为B_n不是正矩阵所以不存在"一致性概念",因此基于评分标度判断矩阵的排序与"一致性"无关.     

ELECTRE: Robust ordinal regression for outranking methods

We present a new method, called ELECTRE^GKMS, which employs robust ordinal regression to construct a set of outranking models compatible with preference information. The preference information supplied by the decision maker (DM) is composed of pairwise comparisons stating the truth or falsity of the outranking relation for some real or fictitious reference alternatives. Moreover, the DM specifies some ranges of variation of comparison thresholds on considered pseudo-criteria. Using robust ordinal regression, the method builds a set of values of concordance indices, concordance thresholds, indifference, preference, and veto thresholds, for which all specified pairwise comparisons can be restored. Such sets are called compatible outranking models. Using these models, two outranking relations are defined, necessary and possible. Whether for an ordered pair of alternatives there is necessary or possible outranking depends on the truth of outranking relation for all or at least one compatible model, respectively. Distinguishing the most certain recommendation worked out by the necessary outranking, and a possible recommendation worked out by the possible outranking, ELECTRE^GKMS answers questions of robustness concern. The method is intended to be used interactively with incremental specification of pairwise comparisons, possibly with decreasing confidence levels. In this way, the necessary and possible outranking relations can be, respectively, enriched or impoverished with the growth of the number of pairwise comparisons. Furthermore, the method is able to identify troublesome pieces of preference information which are responsible for incompatibility. The necessary and possible outranking relations are to be exploited as usual outranking relations to work out recommendation in choice or ranking problems. The introduced approach is illustrated by a didactic example showing how ELECTRE^GKMS can support real-world decision problems.     

Ordinal regression revisited: Multiple criteria ranking using a set of additive value functions

We present a new method, called UTA^GMS, for multiple criteria ranking of alternatives from set A using a set of additive value functions which result from an ordinal regression. The preference information provided by the decision maker is a set of pairwise comparisons on a subset of alternatives A^R ⊆ A, called reference alternatives. The preference model built via ordinal regression is the set of all additive value functions compatible with the preference information. Using this model, one can define two relations in the set A: the necessary weak preference relation which holds for any two alternatives a, b from set A if and only if for all compatible value functions a is preferred to b, and the possible weak preference relation which holds for this pair if and only if for at least one compatible value function a is preferred to b. These relations establish a necessary and a possible ranking of alternatives from A, being, respectively, a partial preorder and a strongly complete relation. The UTA^GMS method is intended to be used interactively, with an increasing subset A^R and a progressive statement of pairwise comparisons. When no preference information is provided, the necessary weak preference relation is a weak dominance relation, and the possible weak preference relation is a complete relation. Every new pairwise comparison of reference alternatives, for which the dominance relation does not hold, is enriching the necessary relation and it is impoverishing the possible relation, so that they converge with the growth of the preference information. Distinguishing necessary and possible consequences of preference information on the complete set of actions, UTA^GMS answers questions of robustness analysis. Moreover, the method can support the decision maker when his/her preference statements cannot be represented in terms of an additive value function. The method is illustrated by an example solved using the UTA^GMS software. Some extensions of the method are also presented.     

Quantum integrability of Beltrami-Laplace operator as geodesic equivalence

Given two Riemannian metrics on a closed connected manifold , we construct self-adjoint differential operators such that if the metrics have the same geodesics then the operators commute with the Beltrami-Laplace operator of the first metric and pairwise commute. If the operators commute and if they are linearly independent, then the metrics have the same geodesics. Received: 11 February 2000; in final form: 20 August 2000/ Published online: 17 May 2001     

On pairwise sensitivity

We define the concept of pairwise sensitivity with respect to initial conditions for the endomorphisms on Lebesgue metric spaces. The idea is that the orbits of almost every pair of nearby initial points (for the product of the invariant measure) of a pairwise sensitive map may diverge from a positive quantity independent of the initial points. We study the relationships between pairwise sensitivity and weak mixing, pairwise sensitivity and positiveness of metric entropy and we compute the largest sensitivity constant.     

A probabilistic interpretation of the final rankings in AHP

The Analytic Hierarchy Process (AHP) has become a popular and practical tool for dealing with complex decision problems. It provides a ranking for the decision alternatives. This article recommends treating the pairwise comparison input data as random variables. This will allow the determination of whether the differences between alternatives are statistically significant.     

Robust ordinal regression for value functions handling interacting criteria

We present a new method called UTA^GMS–INT for ranking a finite set of alternatives evaluated on multiple criteria. It belongs to the family of Robust Ordinal Regression (ROR) methods which build a set of preference models compatible with preference information elicited by the Decision Maker (DM). The preference model used by UTA^GMS–INT is a general additive value function augmented by two types of components corresponding to “bonus” or “penalty” values for positively or negatively interacting pairs of criteria, respectively. When calculating value of a particular alternative, a bonus is added to the additive component of the value function if a given pair of criteria is in a positive synergy for performances of this alternative on the two criteria. Similarly, a penalty is subtracted from the additive component of the value function if a given pair of criteria is in a negative synergy for performances of the considered alternative on the two criteria. The preference information elicited by the DM is composed of pairwise comparisons of some reference alternatives, as well as of comparisons of some pairs of reference alternatives with respect to intensity of preference, either comprehensively or on a particular criterion. In UTA^GMS–INT, ROR starts with identification of pairs of interacting criteria for given preference information by solving a mixed-integer linear program. Once the interacting pairs are validated by the DM, ROR continues calculations with the whole set of compatible value functions handling the interacting criteria, to get necessary and possible preference relations in the considered set of alternatives. A single representative value function can be calculated to attribute specific scores to alternatives. It also gives values to bonuses and penalties. UTA^GMS–INT handles quite general interactions among criteria and provides an interesting alternative to the Choquet integral.