一种考虑决策者风险偏好的区间数多属性决策方法

针对属性值以区间数形式给出的多属性决策问题,提出了一种决策分析方法。在本文中,首先描述了属性值为区间数形式的多属性决策问题;然后通过引入决策者的风险偏好因子将区间数决策信息映射为实数值决策信息,并依据属性值与属性均值绝对偏差的大小确定了属性的权重,在此基础上依据所得权重给出了基于加权和法的方案排序方法,通过对风险偏好因子的不同取值还可进行方案排序的灵敏度分析。最后,通过一个算例说明了本文给出方法的可行性和有效性。     

基于证据推理和前景理论的区间多属性决策方法

针对属性值为区间确定因子结构的多属性决策问题,结合决策者的行为特征,提出了基于证据推理和前景理论的区间多属性决策方法。首先,根据前景理论给出各方案在各属性下的区间前景值。然后,根据区间确定因子规则库推理,得到各方案的合成前景值。最后,根据基于TOPSIS的区间数排序方法对合成前景值进行排序,根据排序结果选择可行方案。文章通过算例说明所提方法具有实用性和有效性。     

不确定性多属性决策的新方法

本文研究了属性指标值，属性权重为L—R模糊数的多属性决策问题，首先在不同的α水平下将L—R模糊数转化为区间数，基于优化模型求出方案的区间属性值并利用α-截及区间数序关系的可能度，构造互补判断矩阵。提出一种新的排序公式，得到一族排序向量，然后对不同α水平下的排序向量集结，得出总的排序向量，以此对方案排序，最后通过实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．     

基于后悔理论的三参数区间灰数信息下的风险型决策方法

针对决策属性值为三参数区间灰数的风险型决策问题,考虑到决策者的有限理性,提出基于后悔理论的风险型决策方法.首先,提出新的三参数区间灰数距离测度和三参数区间灰数的相对核,并构建出感知效用矩阵;然后,将其中的感知效用值集结为各方案的综合感知效用值,并根据各自然状态的风险概率得出各方案的期望效用,由此实现方案排序;最后,通过算例对比分析说明方法的合理性和有效性.     

基于前景理论的三参数区间灰数信息下多属性灰关联决策方法

针对决策信息为三参数区间灰数的多属性决策问题,考虑决策者主观风险态度,提出了一种基于前景理论的灰关联决策方法.首先,利用"奖优罚劣"的线性变换算子对原始决策信息进行规范化处理;其次,通过定义三参数区间灰数的相对核来判断其大小,将其融入前景理论给出前景价值函数和权重函数,由此确定正、负理想方案;然后,根据灰关联分析法得到正、负关联系数,进而确定综合相对贴近度实现对方案的排序;最后,由一个实例表明了所提方法的有效性和合理性.     

基于目标规划和相对优势度的区间数互反判断矩阵排序法

针对决策信息以区间数互反判断矩阵形式给出的多目标决策问题.首先,给出了区间数一致性互反判断矩阵、相对优势度等概念.其次,建立一个目标规划模型,通过求解该模型得到区间数互反判断矩阵的权重向量,并利用各方案的相对优势度和进行方案的排序.提出了一种新的区间数互反判断矩阵排序方法,该方法具有操作简便和易于上机实现的特点.最后,通过实例说明方法的可行性和有效性.     

基于理想关联度的不确定多属性决策方法

针对只有部分属性权重信息且属性值以区间数形式给出的不确定多属性决策问题,提出了一种逼近理想关联度的决策分析方法。首先改进了文[4]给出的区间数决策矩阵的规范化方法;然后提出了利用期望-方差区间数排序方法求解理想最优方案;最后依据关联系数矩阵给出了属性权重信息不完全的区间数多属性决策问题的求解方法,其核心是求解线型规划得到属性权重,进而根据各个方案与理想最优方案的综合关联度大小进行排序。特别地,给出了属性权重完全未知的简洁方法,文后的实例验证了方法的可行性和有效性。     

基于前景理论的多属性灰关联决策方法

针对决策信息为三参数区间灰数、属性权重部分未知的多属性决策问题,考虑决策者主观风险态度,提出一种基于前景理论的灰关联决策方法。首先利用奖优罚劣的[-1,1]线性变换算子对原始决策信息规范化处理,由此确定正负理想方案。定义基于三参数区间灰数的关联系数,将其融入到前景理论给出了前景价值函数,构建综合前景值最大化的优化模型,求解最优属性权重,并最终确定方案的排序。最后用一个实例说明决策方法的合理性和有效性。     

属性具有线性优先级的区间数多属性决策方法

针对属性具有线性优先级、属性值为区间数的多属性决策问题进行了决策方法的研究.在属性权重的确定上,采用低级属性的权重值由所有比其高级属性效用值的乘积,并引入决策者的风险态度因子将区间数映射成点值,再经过规范化后得到.接着,给出了属性具有线性优先级的、属性值为区间数的加权算术平均算子,讨论了该算子的相关性质.最后,利用算子对具有线性优先级的区间数多属性决策问题进行算例分析,结果说明方法是有效的.     

考虑决策者风险偏好的区间直觉模糊多属性群决策方法

提出了一种考虑决策者风险偏好且属性权重信息不完全的区间直觉模糊数多属性群决策方法。同时考虑相似度和接近度,确定每一属性的决策者权重。为了考虑决策者风险偏好对决策结果的影响和避免区间直觉模糊矩阵的渐进性,引入了决策者风险偏好系数,将集结后的综合决策矩阵转换成区间数矩阵。然后,为了客观地求出属性权重信息不完全环境下属性的权重,构建了基于区间直觉模糊交叉熵的属性权重目标规划模型,该模型不仅考虑了评价值的偏差,也强调了评价值自身的可信度。最后,通过研发项目选择问题的实例分析说明了所提方法的合理性和优越性。     

基于双参照点的区间型多属性决策方法研究

文章针对属性值为区间数、权重完全未知的多属性决策问题,提出一种基于双参照点的多属性决策方法。首先,描述了双参照点决策问题的广泛性,分析了双参照点的特征及其对决策行为的影响;接着,通过损益值和态度值来计算效用值,并将效用值用于判断备选策略的可行性;再接着,给出基于损益值的赋权法;然后,利用区间TOPSIS法对效用值进行集结和策略排序;最后,通过一个实例证明本文所提出的决策方法的科学性。     

Decision risk analysis for an interval TOPSIS method

TOPSIS is a multi-attribute decision making (MADM) technique for ranking and selection of a number of externally determined alternatives through distance measures. When the collected data for each criterion is interval and the risk attitude for a decision maker is unknown, we present a new TOPSIS method for normalizing the collected data and ranking the alternatives. The results show that the decision maker with different risk attitude ranks the different alternatives.     

On Multiple Criteria Decision Support for Suppliers on the Competitive Electric Power Market

As an active participant of a competitive energy market, the generator (the energy supplier) challenges new management decisions being exposed to the financial risk environment. There is a strong need for the decision support models and tools for energy market participants. This paper shows that the stochastic short-term planning model can be effectively used as a key analytical tool within the decision support process for relatively small energy suppliers (price-takers). A self-scheduling method for the thermal units on the energy market is addressed. A schedule acquired for given preferences can be used as a desired pattern for bidding process. The uncertainty of the market prices is modeled by a set of possible scenarios with assigned probabilities. Several risk criteria are introduced leading to a multiple criteria optimization problem. The risk criteria are well appealing and easily computable (by means of linear programming) but they meet the formal risk aversion standards. The aspiration/reservation based interactive analysis applied to the multiple criteria problem allows us to find an efficient solution (generation scheme) well adjusted to the generator preferences (risk attitude).     

基于直觉模糊集的全区间决策方法

针对属性值为直觉模糊集且属性权重已知的模糊多属性决策问题,本文基于直觉模糊算术加权平均算子,提出了一种基于直觉模糊集的全区间决策方法。全区间决策函数引入了态度指标k,从而可以反映决策者态度的变化,从0到1变化k值,可以在整个区间内挖掘决策信息的变化,与得分函数法和基于距离TOPSIS贴近度方法相比,将过去的点值判断延伸至全区间判断,避免了决策信息的丢失现象,决策更加准确合理。实例计算表明该方法的正确性、有效性和合理性,具有一定的推广借鉴价值。     

一种基于决策者风险态度的区间数多指标方法的注记

本对基于决策风险态度的区间数多指标方法的映射函数的可区分性、理想点的存在性进行了论证，确保了区间数多指标决策方法的正确性，并对决策风险态度因子进行随机化，使此方法更合理，更有深度。     

Decision making under uncertainty with fuzzy targets

This paper discusses the issue of how to use fuzzy targets in the target-based model for decision making under uncertainty. After introducing a target-based interpretation of the expected value on which it is shown that this model implicitly assumes a neutral behavior on attitude about the target, we examine the issue of using fuzzy targets considering different attitudes about the target selection of the decision maker. We also discuss the problem for situations on which the decision maker’s attitude about target may change according to different states of nature. Especially, it is shown that the target-based approach can provide an unified way for solving the problem of fuzzy decision making with uncertainty about the state of nature and imprecision about payoffs. Several numerical examples are given for illustration of the discussed issues.     

A modification of a solution concept of the linear programming problem with interval coefficients in the constraints

We propose a modification of a concept of solving a linear programming problem with interval coefficients in the constraints. The original concept imposes the decision maker a way comparing intervals, our modification—which is an interactive approach, comprising the original one as its special case—gives him more freedom in the choice of the preference relation. Thanks to this flexibility he may be able to find a solution which better suits his needs and attitude towards risk. What is more, our modification corrects a serious drawback of the original method.     

Decision analysis models in reinsurance

Decision analysis models are developed and illustrated for the reinsurance (risk transfer) decisions made by insurance companies. Decision analytic models were found to be useful tools both for structuring multistage reinsurance decisions and for comparing alternative options. The insurer is faced with many possible choices involving reinsurance type and extent, and an expected utility model provided insight both as a screening device and as an evaluation criterion. Decision analytic models appeared to be superior to other approaches such as mean/variance and risk of ruin models both because of their flexibility and their more comprehensive treatment the important elements of the decision, namely the complete claims distribution, the cost of reinsurance and the insurer's risk attitude.