基于模糊多属性决策的目标威胁估计方法

针对目标威胁估计的功能及特点，提出一种属性为区间数且属性权重完全未知，决策者对方案有偏好的多属性决策（MADM）方法．首先给出方案偏好度的计算公式，在综合考虑客观优化排序和决策者对方案有主观偏好的基础上，建立了一种主客观综合属性权重获取模型，使得属性权重信息更加合理地反映实际情况，模型具有较强的泛化能力．最后，通过防空目标威胁估计实例说明了该方法的实用性和有效性．     

基于直觉模糊粗糙集相似度的多属性决策方法

将直觉模糊粗糙集应用于多属性决策问题,提出了基于改进的直觉模糊粗糙集相似度的多属性决策方法。针对现有的直觉模糊粗糙集相似度忽略犹豫度而造成度量不精确的问题,提出了一种改进的直觉模糊粗糙集相似性度量方法,并揭示其若干重要性质。在此基础上,将属性值用直觉模糊粗糙集表示,并通过各个方案与直觉模糊粗糙集正、负理想方案的相似度比较,实现决策方案排序。数值实例表明了该方法的可行性和有效性,其在态势评估、目标识别等信息融合领域有良好的应用前景。     

基于协同度的灰关联VIKOR方法

为防止个别较差指标的消极影响被其他指标所中和,强化指标的协同效应,提高决策的合理性,提出了一种基于协同度的灰关联VIKOR决策方法。以[λ]协同度为基础,进行规范化处理,并根据指标值对方案的整体影响,建立了方案修正因子模型。以方案修正因子和灰关联确定属性权重的乘积作为综合权重;在此基础上使用比TOPSIS更稳定和可靠的VIKOR方法对方案进行择优,并通过算例说明了方法的有效性和可行性。     

基于相似度的多粒度不确定语言群决策方法

针对具有多粒度不确定语言评价信息的多属性群决策问题,提出了一种基于区间二元语义信息处理和矢量相似度的群决策方法,弥补了基于距离测度的决策方法易造成信息混淆的不足。该方法首先使用二元语义转换函数对多粒度区间语言评价信息进行一致化处理;然后通过建立使备选方案对正理想解相似度最大、负理想解相似度最小的最优化模型来获得相应的属性权重;最后利用区间二元语义的集结算子对评价信息进行加权集成,并通过优序数排序法实现对各方案的排序。实例分析说明了该方法的可行性和有效性。     

基于相离度和可能度的偏差最大化多属性决策方法

针对只有部分权重信息且属性值以区间数形式给出的多属性决策问题,提出一种基于区间数相离度和可能度的偏差最大化决策方法。该方法能充分利用规范化评价的先验信息,评价结果客观可靠,不具有主观随意性,且概念清楚、含义明确、易于计算机上实现。最后通过实例说明了该决策方法的可行性和有效性。     

基于相离度和可能度的偏差最大化多属性决策方法

针对只有部分权重信息且属性值以区间数形式给出的多属性决策问题,提出一种基于区间数相离度和可能度的偏差最大化决策方法.该方法能充分利用规范化评价的先验信息,评价结果客观可靠,不具有主观随意性,且概念清楚、含义明确、易于计算机上实现.最后通过实例说明了该决策方法的可行性和有效性.     

基于改进向量相似度的区间数动态多指标决策模型及应用

针对决策信息为区间数的不确定性动态决策问题,在属性权重和时间权重未知的情况下,基于改进向量相似度的方法,构建一种兼顾决策信息和决策偏好的动态多指标决策模型.利用区间型决策信息的相对相似性和属性重要度,构造相对相似度最小规划模型以确定指标权重;在综合考虑决策信息时间价值、决策者偏好的基础上,构建极大熵模型以确定时间权重;结合向量相似度计算存在的缺陷,提出一种基于向量投影思想的向量综合相似度测度方法,从而建立不确性动态决策模型,并通过实例分析检验该模型的合理性和有效性.     

基于时间度的风险型动态灰色多属决策方法

针对方案属性值为区间灰数的动态多属性决策问题,提出了一种基于前景理论的动态多属性决策方法。定义了区间灰数新的距离测度;鉴于被评价对象在时序上的差异信息和波动性,建立了基于熵和时间度的确定时间权重的优化模型;以两两方案互为参考点确定了前景价值函数,由此构建了求解最优权向量的优化模型,最后以方案的综合前景值对方案进行排序。通过实例说明了该方法的合理性和有效性。     

针对构件测试本体的语义相似度计算方法

为了提高构件测试信息的检索效率,针对现有本体语义相似度计算方法作用于构件测试本体时容易出现漏检的问题,提出一种结合本体概念和属性的综合语义相似度计算方法。该方法首先结合概念的结构、层次、子代节点个数和祖先节点个数等因素计算概念相似度;然后,结合属性的概念相似度和数据类型相似度计算属性相似度;最后,综合概念相似度和属性相似度计算本体的语义相似度。实验表明该方法可以有效应用于构件测试领域及其他领域的信息检索。     

基于多指标灰区间数关联决策模型的产品方案设计

针对复杂产品方案设计中属性信息的不完全性和不确定性,研究了方案设计中多指标灰区间数关联决策计算方法.提出一种基于灰色系统理论的多指标灰区间数关联决策模型.该模型通过引入灰区间敷序列的范数实现多指标决策矩阵的规范化处理,构建了综合考虑灰色信息的正负理想区间方案,利用方案的优属度从整体性的角度获得最优决策方案.最后,通过大型水轮机的方案设计,验证了该模型的有效性和实用性.     

Semantic dominance analysis for multicriteria decision‐making problems with unbalanced linguistic scale

The multicriteria decision‐making problem with an unbalanced linguistic scale is analyzed by multicriteria semantic dominance (MCSD) technique. The technique only requires the available partial semantics information about the scale. The MCSD rules on two types of unbalanced linguistic scale are introduced and proven. With these rules, alternatives are divided into two mutually exclusive sets called the efficient set and inefficient set. The decision maker with a specific type of linguistic scale will never choose the alternative from the corresponding inefficient set as the feasible one. Thus he/she can easily choose from the original alternative set. An example is also provided to illustrate the procedure of the proposed method.     

Identifying and eliminating dominated alternatives in multi-attribute decision making with intuitionistic fuzzy information

Multi-attribute decision making under uncertainty is a usual task in our daily life. In the decision making process, the decision information provided by the decision maker (or expert) over alternatives may take the form of intuitionistic fuzzy numbers, and the weight information on attributes is usually incomplete. To this issue, we first transform the original decision matrix, whose elements are intuitionistic fuzzy numbers expressed by pairs of satisfaction degrees and dissatisfaction degrees, into its expected decision matrix, whose elements are composed of satisfaction degrees and hesitation degrees. We introduce the concept of dominated alternative, and give a method to identify the dominated alternatives. Then we develop an interactive method for eliminating any dominated alternatives by updating the decision maker's preferences gradually so as to find out the optimal one eventually. A further extension of the interactive method to interval-valued intuitionistic fuzzy situations is given, and the solution process of this interactive method is shown in detail through an illustrative example.     

区间Pythagorean模糊交互式多准则决策模型

研究了权重信息部分已知,评价信息为区间Pythagorean模糊数的交互式多准则决策问题。利用区间Pythagorean模糊数得分函数,计算各方案的加权得分向量在Pythagorean模糊正理想点和Pythagorean模糊负理想点上的投影,构建基于方案满意度最大的非线性规划准则权重确定模型。根据决策者的主观偏好并结合现有客观信息建立单目标规划模型,通过对方案满意度的给定与修正来实现交互决策。通过算例说明模型及方法的可行性和有效性。     

Returns to scale and scale elasticity in the presence of weight restrictions and alternative solutions

In this paper some new results about two important topics in performance analysis, including scale elasticity (SE) and returns to scale (RTS), in the presence of weight restrictions and alternative solutions are proved. Since SE and RTS help managers to make decisions about the expansion or contraction of the operation of decision making units under assessment, the established results can be useful from both theoretical and applied points of view. The provided implications are devoted to some mathematical characterizations and properties of SE and RTS as well as their relationships.     

The fuzzy dual: Information for the multiple objective decision-maker

In this article the dual of the multiple objective linear programme is used as a basis for an interactive method for decision making. The information presented to the DM (decision maker) at each stage arises naturally from the structure of the problem and only requires the DM to recognize the appropriateness of alternative decisions and feasible changes thereto. He does not have to construct any explicit preference functions.     

A knowledge-based expert system for technology acquisition in small and medium scale manufacturing organizations

Consistent and reliable decision making for technology acquisition in small and medium scale manufacturing organizations is vitally important since these firms are the backbone of national economies, both in developed and developing countries. Because of their flexibility, small and medium scale firms are successful in adopting new technologies. However, a careful analysis should be conducted in technology acquisition decisions. Since these decisions require special type of knowledge and expertise, expert system, as an important tool of computerized decision making, can overcome these multidimensional difficulties.

This paper proposes a knowledge-based approach making use of issues such as sales, processes, costs and general policies, in decision processes for technology acquisition by small and medium scale manufacturing organizations in the developing environments.     

基于方案修订的群决策一致性形成的研究

层次分析法(AHP)是群决策中经常使用的一种方法,利用AHP进行群决策的过程实质上也是决策者个体偏好集结的过程。针对如何将不同形式的偏好信息进行有效集结以形成群决策一致性方案的问题,提出一种通过活用AHP修订决策方案达到决策者群体的一致性偏好最终得以形成的方法,在利用决策者的决策信息进行群组划分的基础上明确各个划分的决策偏好差异,提出了活用AHP进行群决策一致性形成的方向,并形成了有效的动态群决策过程。     

Multitime scale Markov decision processes

This paper proposes a simple analytical model called M time scale Markov decision process (MMDPs) for hierarchically structured sequential decision making processes, where decisions in each level in the M-level hierarchy are made in M different discrete time scales. In this model, the state-space and the control-space of each level in the hierarchy are nonoverlapping with those of the other levels, respectively, and the hierarchy is structured in a "pyramid" sense such that a decision made at level m (slower time scale) state and/or the state will affect the evolutionary decision making process of the lower level m+1 (faster time scale) until a new decision is made at the higher level but the lower level decisions themselves do not affect the transition dynamics of higher levels. The performance produced by the lower level decisions will affect the higher level decisions. A hierarchical objective function is defined such that the finite-horizon value of following a (nonstationary) policy at level m+1 over a decision epoch of level m plus an immediate reward at level m is the single-step reward for the decision making process at level m. From this we define "multi-level optimal value function" and derive "multi-level optimality equation." We discuss how to solve MMDPs exactly and study some approximation methods, along with heuristic sampling-based schemes, to solve MMDPs.     

基于OWA算子的不同形式偏好信息的群决策方法

研究具有不同形式偏好信息的群决策问题.在描述效用值、序关系值、模糊判断矩阵和AHP判断矩阵等4种形式偏好信息的基础上,首先给出将不同形式的偏好信息转化为模糊判断矩阵形式的计算公式,然后基于OWA算子给出集结各决策者偏好信息和方案优选的方法,最后用一个算例证明了所提出方法的有效性.     

权重信息完全未知的二维二元语义多属性群决策方法

针对群决策问题中专家权重和属性权重均未知的情形,提出一种基于二维二元语义表示模型的多属性群决策方法.首先,考虑到不同决策者对二维二元语义信息中第一维信息和第二维信息的相对重要性比重不同,提出一种能够反映出该比重变化对于二维二元语义间比较和距离测度影响的得分函数和距离公式;其次,利用得分函数和距离公式建立目标函数,依据专家意见的熵值确立约束条件,进而构建能够同时求解出专家权重和属性权重的双权重求解模型,再分别针对不同的方案依次进行求解,得到每一个方案假定为最优方案时相应的权重信息;再次,按照所提出的新方法,综合目标函数值的大小对方案进行排序与择优;最后,通过案例分析与对比验证所提方法的有效性和科学性.