决策支持下的不完全偏好信息多目标对策

针对多目标对策的不完全偏好信息,将理性策略概念和偏好规划理论引入到多目标对策研究中,把两人的多目标对策考虑为两个局中人同时面临的两个多目标决策问题,偏好信息用可行权重限定集合进行建模.多目标对策模型分为对策模型和决策模型两部分.在对策模型中,利用理性和偏好的共同知识,获得理性策略集.在决策模型中,局中人将策略选择作为使用私人偏好信息的多目标决策问题.最后,通过实例验算表明所提方法的有效性.     

部分权重信息下对方案有互补偏好的多属性决策法

研究了只有部分权重信息且对方案的偏好信息以模糊互补判断矩阵形式给出的多属性决策问题.首先,基于模糊互补判断矩阵的主观偏好信息,利用转换函数将客观决策信息一致化,建立一个目标规划模型,通过求解该模型得到属性权重,从而利用加性加权法获得各方案的综合属性值,并以此对方案进行排序或择优.提出了一种基于目标规划的多属性决策方法.该方法具有操作简便和易于上机实现的特点.最后,通过实例说明模型及方法的可行性和有效性.     

多属性决策中的目标规划

针对只有部分权重信息的对方案有偏好的多属性决策问题,本文给出了一种简单的目标规划模型,通过对该模型的求解却可得到决策方案的排序。最后给出了一个算例。     

项目投资的交互式决策分析

本文以某个企业技改项目投资决策为例,给出了一个交互式多目标决策过程.该过程充分考虑了企业进行决策时的实际情况及环境和人的主观偏好,所得结果更合理.     

基于UTA方法的关键基础设施系统的保护研究

关键基础设施系统是城市的生命线,但常因突发事件频发而具有不稳定性和脆弱性。一个好的保护方案应该综合考虑关键基础设施系统的韧性和成本等多个目标,但这些目标常常相互冲突而使决策陷入困境。本研究从多目标优化角度入手,探索用UTA方法确定保护关键基础设施系统最佳方案的可行性,UTA法通过与决策者互动获取决策者的偏好信息,并基于线性规划和价值函数原理构建了决策者偏好模型。通过C县电网系统的案例分析发现UTA方法可帮助决策者在决策过程中考虑多目标之间的冲突与权衡,从而确定最满意的决策方案。     

基于UTA方法的多目标优化模型

针对多目标线性优化问题进行研究,提出了一种基于效用加性方法(UTA)的多目标线性优化方法.利用不同目标值的组合给出训练方案,决策者针对训练方案给出一些偏好信息,据此推断决策者的效用函数,并进一步求解多目标线性优化模型.进一步给出了算例来说明方法的实施过程及验证可行性.方法较多的考虑了决策者对于决策的偏好,注重决策者的意见,为多目标决策问题提供了一种新的思路.     

决策者具有(严格)凸性偏好结构下的一类交互式多目标决策方法

为了更好地解决决策者具有(严格)凸性偏好结构下的多目标决策问题,一般目标空间为有界凸域的情形常常可以转化为目标空间为有界闭凸区域的情形,首先分析了切割平面及该平面上偏好最优点与被切割平面分割成的为有界闭凸区域的目标空间或目标空间的子集的两个部分之间的关系;然后分析并指出了对于包含全局偏好最优目标方案点的为有界闭凸域的目标空间及其子集(准最优目标集),在确定了切割平面上的偏好最优点后,通过适当地选取供决策者与切割平面的偏好最优点进行比较判断的目标方案点,经过一次比较就可以确定一个新的范围更小的包含全局偏好最优目标方案点的目标空间的有界闭凸子区域(准最优目标集).为获取切割平面上的偏好最优点,提出了改进的坐标轮换法.在这些结论和方法的基础上,提出了决策者具有(严格)凸性偏好结构下的一类交互式多目标决策方法,要求决策者提供较易的偏好性息,决策效能较好.     

监督模糊模式识别交叉迭代模型

从模糊模式识别概念出发，建立一种以决策者经验、偏好为监督，在方案优属等级识别过程中确定最佳目标权重和方案优属度的监督模糊模式识别交叉迭代算法，该算法集成了决策偏好信息完全未知、部分未知、完全已知的主客观权重识别方法。并严格证明了该算法的局部收敛性。     

偏好信息为模糊互反判断矩阵的模糊多属性决策法

研究只有部分权重信息且决策者对方案的偏好信息以模糊互反判断矩阵形式给出的模糊多属性决策问题。提出了一种基于目标规划模型的模糊多属性决策方法。该法首先基于模糊互反判断矩阵，利用转换函数将决策信息一致化，建立了一个目标规划模型．通过求解该模型确定属性的权重，然后运用加性加权法求出各方案的模糊综合属性值，并利用已有的三角模糊数排序公式求得决策方案的排序。文章最后把该法应用于解决风险投资领域中的项目评估问题。     

犹豫直觉模糊偏好关系积性一致性及其在群决策中的应用

模糊偏好关系在群决策中得到了广泛研究,针对犹豫直觉模糊集既能反映决策者偏好和非偏好的信息,又能描述其犹豫心理的特点,提出了犹豫直觉模糊偏好关系及其积性一致性的定义。为了修复不一致的犹豫直觉模糊偏好关系,先构建积性一致性指标,然后提出两种修复方法。最后,将犹豫直觉模糊偏好关系应用到群决策中,通过实例和比较说明了两种修复方法的有效性和合理性。     

基于决策者信任水平和组合赋权的不完全偏好复杂大群体应急决策方法

针对属性权重完全未知且专家偏好出现残缺值的复杂大群体应急决策问题,提出了一种新的决策方法。首先,设计了一套基于决策者信任水平的残缺值填充机制,对缺失的偏好信息进行补充。然后,将各方案的大群体偏好信息进行聚类,基于方案信息熵和群体偏好冲突水平构建组合赋权方法,对属性权重进行测算,进而得到各个方案的综合评价值。最后对该方法进行了实例验证,验证结果表明本文提出的方法具有良好的可行性和有效性。     

基于集对分析的多种不确定偏好形式大群体决策方法

针对具有多种不确定偏好形式的多方案大群体决策问题,提出一种基于集对分析的群决策方法。将区间数、三角模糊数以及语言值三种形式的不确定偏好转换为联系数,保留了不确定偏好信息中的确定性与不确定性。提出一种区间聚类算法,在决策成员权重未知的情况下对成员进行赋权。利用加权综合联系数对大群体偏好进行集结,根据方案的集对势大小给出方案的排序。该方法避免了确定权重时的主观性,同时考虑决策信息的确定性与不确定性,提高了决策结果的可信度。通过实例分析验证了方法的有效性和实用性。     

Group decision making based on intuitionistic multiplicative aggregation operators

Preference relations are the most common techniques to express decision maker’s preference information over alternatives or criteria. To consistent with the law of diminishing marginal utility, we use the asymmetrical scale instead of the symmetrical one to express the information in intuitionistic fuzzy preference relations, and introduce a new kind of preference relation called the intuitionistic multiplicative preference relation, which contains two parts of information describing the intensity degrees that an alternative is or not priority to another. Some basic operations are introduced, based on which, an aggregation principle is proposed to aggregate the intuitionistic multiplicative preference information, the desirable properties and special cases are further discussed. Choquet Integral and power average are also applied to the aggregation principle to produce the aggregation operators to reflect the correlations of the intuitionistic multiplicative preference information. Finally, a method is given to deal with the group decision making based on intuitionistic multiplicative preference relations.     

不同直觉偏好信息下的多属性决策方法

研究了属性值为实数且决策者对属性的偏好信息以直觉判断矩阵或残缺直觉判断矩阵给出的模糊多属性决策问题.首先介绍了直觉判断矩阵、一致性直觉判断矩阵、残缺直觉判断矩阵、一致性残缺直觉判断矩阵等概念,而后分别考虑关于直觉判断矩阵和残缺直觉判断矩阵的多属性决策问题,接着建立了基于直觉判断矩阵和残缺直觉判断矩阵的多属性群决策模型,通过求解这些模型获得属性的权重.进而给出了不同直觉偏好信息下的多属性决策方法.最后通过一个例子说明了该方法的可行性和实用性.     

考虑可信度和属性优先级的犹豫模糊决策方法

研究了考虑可信度的犹豫模糊混合集成因子以及考虑属性优先级的犹豫模糊多属性决策方法。首先给出了用于衡量数据差异程度的加权变异率公式,并证明了其具有类似于基尼系数的优良度量性质,之后在此基础上提出了可信度诱导犹豫模糊混合平均(CIHFHA)算子。针对属性权重信息未知的犹豫模糊决策问题,构建了一种新的考虑属性优先级的熵值修正G1的组合赋权方法,该方法可有效地利用属性客观评价数据以及通过考虑属性优先级体现专家意见,解决了主客观权重分配问题,得出的属性权重更加客观、合理。之后给出了一种基于CIHFHA算子和组合赋权方法的多属性决策方法,算例说明该方法的有效性和实用性。     

三角模糊偏好下冲突型多属性群决策方法研究

针对三角模糊偏好下冲突型群决策问题,本文提出一种新的决策方法。在冲突消解阶段,用三角模糊数表示决策专家偏好,定义两三角模糊数型偏好矢量间的相似度,通过计算专家对各个方案的偏好矢量与各方案的群偏好矢量间的相似度,以此为基础定义专家的冲突测度。给出阈值和协商机制调控专家的冲突测度,直到所有的专家的冲突测度都小于给定阈值,进入决策阶段。在决策阶段,利用三角模糊数的期望函数确定属性权重,计算各个方案群偏好矢量与理想方案偏好矢量之间的加权相似度,由加权相似度大小排列决策,选出最优方案。最后给出案例应用,利用Matlab画出各方案的冲突测度图,数值结果表明本文方法的可行性及有效性。     

Multi-attribute group decision-making with multi-granularity linguistic assessment information: An improved approach based on deviation and TOPSIS

With respect to group decision-making problems with multi-granularity linguistic assessment information, a new approach is proposed. Firstly, the computational formulae are given in order to transform and unify the multi-granularity linguistic comparison matrices. Secondly, the method of standard and mean deviation is applied to determine the unknown attribute weights, and the weights of the decision makers will be determined by using the extended TOPSIS (technique for order preference by similarity to an ideal solution) method. Finally, based on the LWAA (linguistic weighted arithmetic averaging) operator, information on the preference provided by each decision maker is aggregated into the comprehensive evaluation value of each alternative, and the most desirable alternative is selected. The proposed approach expands the research in multi-attribute group decision-making with multi-granularity linguistic assessment information by both considering the weights of the attributes and decision makers, and objective weighting for them. A numerical example is given to illustrate the practicability and usefulness of the proposed approach.     

Ranking multicriteria alternatives: The method ZAPROS III

The new version of the method for the construction of partial order on the set of multicriteria alternatives is presented. This method belongs to the family of verbal decision analysis (VDA) methods and gives a more efficient means of problem solution. The method is based on psychologically valid operations for information elicitation from a decision maker: comparisons of two distances between the evaluations on the ordinal scales of two criteria. The information received from a decision maker is used for the construction of a binary relation between a pair of alternatives which yields preference, indifference and incomparability relations. The method allows construction of a partial order on the set of given alternatives as well as on the set of all possible alternatives. The illustrative example is given.     

An avoiding information loss approach to group decision making

Owing to the increasing complexity in various management, aggregating experts’ knowledge and experiences to make an appropriate decision is an important research area. However, with aggregation of information in decision process, some information may be lost. The aim of this paper is to present a systematic methodology avoiding information loss for group decision making. An extended TOPSIS method is twice used to the current method, which is first used to determine the weights of decision makers, and second used to rank the preference order of alternatives. The proposed approach is straightforward and has no aggregation of information. A comparison of proposed method with other methods is also done. Finally, a numerical example for supplier selection is given to illustrate the application of the introduced method.     

An integrated model-based interactive approach to FMAGDM with incomplete preference information

Incomplete fuzzy preference relations, incomplete multiplicative preference relations, and incomplete linguistic preference relations are very useful to express decision makers’ incomplete preferences over attributes or alternatives in the process of decision making under fuzzy environments. The aim of this paper is to investigate fuzzy multiple attribute group decision making problems where the attribute values are represented in intuitionistic fuzzy numbers and the information on attribute weights is provided by decision makers by means of one or some of the different preference structures, including weak ranking, strict ranking, difference ranking, multiple ranking, interval numbers, incomplete fuzzy preference relations, incomplete multiplicative preference relations, and incomplete linguistic preference relations. We transform all individual intuitionistic fuzzy decision matrices into the interval decision matrices and construct their expected decision matrices, and then aggregate all these expected decision matrices into a collective one. We establish an integrated model by unifying the collective decision matrix and all the given different structures of incomplete weight preference information, and develop an integrated model-based approach to interacting with the decision makers so as to adjust all the inconsistent incomplete fuzzy preference relations, inconsistent incomplete linguistic preference relations and inconsistent incomplete multiplicative preference relations into the ones with acceptable consistency. The developed approach can derive the attribute weights and the ranking of the alternatives directly from the integrated model, and thus it has the following prominent characteristics: (1) it does not need to construct the complete fuzzy preference relations, complete linguistic preference relations and complete multiplicative preference relations from the incomplete fuzzy preference relations, incomplete linguistic preference relations and incomplete multiplicative preference relations, respectively; (2) it does not need to unify the different structures of incomplete preferences, and thus can simplify the calculation and avoid distorting the given preference information; and (3) it can sufficiently reflect and adjust the subjective desirability of decision makers in the process of interaction. A practical example is also provided to illustrate the developed approach.