基于区间数决策矩阵的评判专家水平分析方法

在群决策分析中,如何评判专家水平是一个重要课题,针对群决策中基于区间数决策矩阵形式偏好信息的评判专家水平问题,提出了一种分析方法。首先,给出了有关区间数、专家群体区间数决策矩阵的定义及其决策矩阵的规范化方法;然后,通过定义专家与专家群体关于方案排序向量之间的偏差,给出了基于理想点法的区间数决策矩阵形式偏好信息的专家评判水平的分析方法。同时,利用聚类分析方法,给出了专家评判水平分类的判别方法;最后,通过一个算例说明给出的分析方法。     

基于AHP的群决策排名问题

针对排名结果是由分差大的那部分评委主导,分差小的评委的决策意见往往被湮没的问题给出基于AHP的群决策排名方法.详细介绍了多属性群决策专家权重确定的方法、属性权重确定的方法和信息集结的方法.     

Treating measurement uncertainty in industrial conformity control

Every conformity control method based on measurements is subject to uncertainty, which distorts the decision. In the traditional conformity control approaches, this uncertainty is an inherent part of the deviation of the observed characteristic; however, the distribution of the real product characteristic may differ from the distribution of measurement uncertainty, which obscures the real conformity or nonconformity. The specification and consideration of this uncertainty are particularly necessary if it is high and/or the consequences associated with the decision errors are severe. This paper studies the effects of the cost structure associated with the decision outcomes and the skewness and kurtosis of the measurement uncertainty distribution. The proposed method can specify when and how the measurement uncertainty should be taken into account to increase the expected profit associated with the decision.     

A method for group decision-making based on determining weights of decision makers using TOPSIS

In general, weights of decision makers (DMs) play a very important role in multiple attribute group decision-making (MAGDM), how to measure the weights of DMs is an interesting research topic. This paper presents a new approach for determining weights of DMs in group decision environment based on an extended TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method. We define the positive ideal solution as the average of group decision. The negative ideal solution includes two parts: left and right negative ideal solution, which are the minimum and maximum matrixes of group decision, respectively. We give an example to illustrate the developed approach. Finally, the advantages and disadvantages of this study are also compared.     

A Goal Programming model of the reference point method

Real-life decision problems are usually so complex they cannot be modeled with a single objective function, thus creating a need for clear and efficient techniques of handling multiple criteria to support the decision process. The most commonly used technique is Goal Programming. It is clear and appealing, but in the case of multiobjective optimization problems strongly criticized due to its noncompliance with the efficiency (Pareto-optimality) principle. On the other hand, the reference point method, although using similar control parameters as Goal Programming, always generates efficient solutions. In this paper, we show how the reference point method can be modeled within the Goal Programming methodology. It allows us to simplify implementations of the reference point method as well as shows how Goal Programming with relaxation of some traditional assumptions can be extended to a multiobjective optimization technique meeting the efficiency principle.     

Behavioral multi-criteria decision analysis: the TODIM method with criteria interactions

In this paper a multi-criteria decision aiding model is developed through the use of the Choquet integral. The proposed model is an extension of the TODIM method, which is based on nonlinear Cumulative Prospect Theory. The paper starts by reviewing the first steps of behavioral decision theory. A presentation of the TODIM method follows. The basic concepts of the Choquet integral as related to multi-criteria decision aiding are reviewed. It is also shown how the measures of dominance of the TODIM method can be rewritten through the application of the Choquet integral. From the ordering of decision criteria the fuzzy measures of criteria interactions are computed, which leads to the ranking of alternatives. A case study on the forecasting of property values for rent in a Brazilian city illustrates the proposed model. Results obtained from the use of the Choquet integral are then compared against a previously made usage of the TODIM method. It is concluded that significant advantages exist derived from the use of the Choquet integral. The paper closes with recommendations for future research.     

Pseudo-criteria versus linear utility function in stochastic multi-criteria acceptability analysis

Stochastic multi-criteria acceptability analysis (SMAA) is a multi-criteria decision support method for multiple decision-makers (DMs) in discrete problems. SMAA does not require explicit or implicit preference information from the DMs. Instead, the method is based on exploring the weight space in order to describe the valuations that would make each alternative the preferred one. Partial preference information can be represented in the weight space analysis through weight distributions. In this paper we compare two variants of the SMAA method using randomly generated test problems with 2–12 criteria and 4–12 alternatives. In the original SMAA, a utility or value function models the DMs' preference structure, and the inaccuracy or uncertainty of the criteria is represented by probability distributions. In SMAA-3, ELECTRE III-type pseudo-criteria are used instead. Both methods compute for each alternative an acceptability index measuring the variety of different valuations that supports this alternative, and a central weight vector representing the typical valuations resulting in this decision. We seek answers to three questions: (1) how similar are the results provided by the decision models, (2) what kind of systematic differences exists between the models, and (3) how could one select indifference and preference thresholds of the pseudo-criteria model to match a utility model with given probability distributions?     

On consistency measures of linguistic preference relations

Inspired by the concept of deviation measure between two linguistic preference relations, this paper further defines the deviation measure of a linguistic preference relation to the set of consistent linguistic preference relations. Based on this, we present a consistency index of linguistic preference relations and develop a consistency measure method for linguistic preference relations. This method is performed to ensure that the decision maker is being neither random nor illogical in his or her pairwise comparisons using the linguistic label set. Using this consistency measure, we discuss how to deal with inconsistency in linguistic preference relations, and also investigate the consistency properties of collective linguistic preference relations. These results are of vital importance for group decision making with linguistic preference relations.     

Possibility and cost in decision analysis

The thesis of this paper is that a practically relevant decision theory must be based on the concept of possibility. As the concept is interpreted here it covers all the obstacles the decision-maker is facing. In many situations the contemplation of possibility is quite as relevant as the usual concentration on utility and probability. There is a traditional economic concept which conforms to an emphasis on obstacles or possibility in decision-making: opportunity cost. The opportunity cost of a decision is the value of the highest valued possible decision which is inhibited as a result of the decision actually taken. However as opportunity cost is usually interpreted decisions are dichotomized as either possible or impossible to perform. It is argued in the paper that this dichotomization is not very realistic. In reality there must be allowed for a continuum of states between the plain impossibility and the complete possibility. This gradual view of possibility could be dealt with if the fuzzy set theory is used. In the paper it is shown how some relevant concepts regarding possibility could be based on fuzziness and how these concepts could be used to analyze practical situations. A method to deal simultaneously with possibility and probability is stated.     

Structured risk management: filling a gap in decision analysis education

Risk management is a standard management tool that does not generally appear in decision analysis textbooks nor is it explicitly cited as part of the standard decision-analysis paradigm. In contrast, risk management articles and books describe how decision trees can be used to evaluate specific risk management strategies. In this paper we describe a series of steps that should be a routine part of every decision tree analysis. They are designed to assess the expected value of developing a risk management strategy with regard to different aspects of uncertainty. The method is intended to trigger a focused brainstorming session to search for specific strategies to manage targeted risks. The procedure adds structure to the value-enhancing dimension of decision analysis that creates new strategies with less risk and higher expected values. The material presented here can easily be incorporated into even an overview of decision analysis in a survey class of operational research.     

一种使用在线评论信息的商品购买决策分析方法

在线评论信息对消费者的商品购买决策影响非常显著,如何使用数据体量较大的在线评论信息来进行有针对性的商品购买决策分析是近年来尤为需要关注的一个新研究内容。本文提出一种使用在线评论信息的商品购买决策分析方法。首先,通过在线评论信息的挖掘来确定了消费者所重点关注的关于候选商品的商品特征及其权重;然后,通过消费者情感的分析来构建了关于各候选商品的商品购买决策矩阵;在此基础上,通过给出的一种基于随机TOPSIS的方案排序方法来进行了各候选商品的排序。最后,依据携程网提供的关于三家客栈的在线评论信息进行了数据实验,从而说明了本文提出方法的实用性与可行性。     

一种PROMETHEE Ⅱ权重的敏感性分析方法

以往MADM的敏感性分析主要研究的是使方案集排序稳定的参数区间。本文针对PROMETHEEⅡ方法的权重建立一种新的敏感性分析数学模型，利用经典的线性规划方法，求解使得某方案排序第一且变化最小的权重值，回答了权重超出稳定区间后排序改变方向的问题。在实际应用中，有利于帮助决策者及时调整权重，得到合理结果。     

基于二元语义评价信息的个体优势特征识别方法

本文依据群体语言评价信息特点,基于二元语义信息处理、理想点评价模型及聚类分析等方法,给出了基于二元语义评价信息并适用于层次结构的个体优势特征识别方法;对某企业的文化优势特征进行识别,演示了方法的使用过程,并说明了所提方法的可行性和有效性。从二元语义的评价信息中,本方法能够比较充分地挖掘和体现被测行为主体的个体优势特征,能够为决策者提供多种维度的决策信息。     

多指标决策的层次分析与模糊分析相结合的综合评价法

心理测评中各项指标均带有模糊性,并且由于指标多,问题复杂,用这些指标来分析、评价人的素质、潜力等,基本上还是依赖专家逐个分析,得出评价结果。文章通过层次分析法来体现专家思维中的偏好信息,由贴近度来量度个体测试数据与理想区域的综合接近程度,并通过两者结合给出优劣排序,为专家决策提供一个综合的带有偏好信息的评价结果     

Determining new possible weight values in PROMETHEE: a procedure based on data envelopment analysis

Operational research (OR) offers efficient tools to support managers in strategic decision-making processes. Data envelopment analysis (DEA) and multiple criteria decision aid (MCDA) are two important research areas in OR. These two domains are both based on the evaluation of “objects” according to multiple “points of views”. Within the MCDA framework, choosing appropriate weights for the different criteria often arises as a problem itself for decision makers. As a consequence, researchers have developed original methodologies to help them during this elicitation phase. In this work, we aim to investigate how DEA can be used to propose weights in the context of the PROMETHEE II method. More precisely, we suggest an extension of the so-called “decision maker brain” used in the GAIA plane (also known as PROMETHEE VI) based on DEA. The underlying idea is based on the computation of weights in PROMETHEE (GAIA brain) which are compatible with the DEA analysis. We end this paper with a numerical example.     

碳排放税收政策下供应链网络成员企业行为研究

针对三种碳税决策框架:分权碳税框架、集权碳税框架——固定阀值、集权碳税框架——弹性阀值,分别分析三种碳排放税收政策决策框架下供应链网络中成员企业收益的变化以及各企业间的交互行为,给出了各成员企业的均衡条件,并将其转化为变分不等式问题,建立碳排放税收政策下供应链网络成员企业博弈模型,并提出基于欧拉算法的模型求解方法。最后结合算例分析碳排放税收政策下供应链网络成员企业关于生产决策、分销决策、碳排放量的反应,研究为达到预期的环境目标,政府相关部门如何调整单位碳排放税,同时,根据成员企业相关经济指标的均衡结果,政府相关部门又如何调整碳排放的环境目标。     

Tentative guidelines to help choosing an appropriate MCDA method

Despite the development of a large number of refined multicriterion decision aid (MCDA) methods, none can be considered as the `super method' appropriate to all decision making situations. Hence, how can one choose an appropriate method to a specific decision situation? Recent experimental studies in psychology and behaviour have revealed, on the one hand, that the human thinking is not to be modelled by logical rules and calculations, and, on the other hand, that the response mode affects the preference formation as well as the use of compensatory or noncompensatory strategies. The aim of this paper is to draw a conceptual framework for articulating tentative guidelines to choose an appropriate MCDA method. This paper also presents the results of the comparison of well known multicriterion aggregation procedures (MCAP) on the basis of these guidelines. In our opinion this study can constitute a first step for proposing a methodological approach to select an appropriate MCDA method to a specific decision making situation. Such an approach should be validated and may be integrated into a decision support system. Moreover, the framework suggested is helpful to develop useful methods and to address neglected issues within the field.     

Fuzzy decision trees

We propose here to extend the decision trees method to the case when the involved data (probabilities, cost, profits, losses) appear as words belonging to the common language whose semantic representations are fuzzy sets. First we discuss the reasons why such an extension is to be aimed at. Then in the fuzzy case we carry out a reformalization of the basic concepts of probability and utility theory. Finally we show how these reformalized concepts can be applied to fuzzy decision trees.     

影响收益的公司指标在最优投资组合选择中的应用

如何从数目巨大的市场股票集中选取一组特定的股票作为最优投资组合选择模型的输入,以确保最终的投资方案具有优异而稳定的表现一直是投资理论界和实务界关注的重点.为此,本文基于作者新近结合中国股市特性并采用新方法所确定影响中国股票收益的多个公司基本特性指标,设计了一个恰当的股票预选策略,并由此导出了新型而稳健的投资组合选择两阶段法.实证结果表明新方法能使投资者便捷地找到更稳健的投资策略.     

基于本体的决策问题智能分析方法及其应用

在决策支持系统(DSS)中,决策问题分析理解的目的是识别决策问题的求解方法,以辅助用户快速求解问题,制定决策方案。为了提高DSS对决策问题分析理解的智能性和准确性,采用本体方法,定义了决策问题知识的本体概念结构,提出了一种基于本体的决策问题类型智能识别方法。最后,通过一个应用实例说明了该方法的具体分析过程,验证了该方法的有效性。