WaveLAN+LAN船舶编队网络环境下的评估系统研究

WaveLAN+LAN编队网络环境下的评估系统设计方案。采用Browser/Server模式组织数据,应用多目标决策、模糊综合评判等方法对所建立的系统数学模型进行评估计算,为水下探测器试验择优方案系统提供定量依据。     

水利工程施工方案优选方法研究

在分析水利工程的特点和目标要求的基础上,研究了灵敏度分析、多目标规划、模糊多属性决策3种方法在施工方案优选中应用的优点和缺点,提出模糊多属性决策法在施工方案优选中的应用具有一定的适用性和优点,并介绍了模糊多属性决策的计算方法.     

基于FAHP和FMCDM构建软件可信性评估模型*

结合软件可信性评估的特点及模糊理论的最新进展,提出一种基于模糊层次分析法和模糊多指标决策理论的评估模型。首先针对软件可信性没有一致定义的现状,提出了相对可信性的概念;接着基于模糊数理论,用三角模糊数表示专家评估中语言变量的主观性和模糊性,结合专家给出的模糊指标权重及待评软件可信等级的模糊评价,得到软件可信性的集成模糊评价;最后,将该模型应用到国内某汽车制造企业整车产品开发项目管理软件评估中,实例说明软件可信性评估的具体过程,结果验证了该模型的实效性。     

水利工程施工方案优选方法研究

在分析水利工程的特点和目标要求的基础上，研究了灵敏度分析、多目标规划、模糊多属性决策3种方法在施工方案优选中应用的优点和缺点，提出模糊多属性决策法在施工方案优选中的应用具有一定的适用性和优点，并介绍了模糊多属性决策的计算方法。     

基于Vague集模糊一致关系的多目标模糊决策

基于Vague集理论和模糊一致关系理论,提出了一种新的多目标模糊决策方法。这种决策方法综合考虑方案满足目标条件的可能性、不满足的可能性和未知的可能性三个方面的因素,分别对每个目标条件建立模糊优先关系矩阵和模糊一致矩阵,最后得出用于评估每种方案的真、假两方面的优度值,从支持和反对两方面来进行综合评估,给出方案的优劣程度排序,从而选出最优的方案。     

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。     

概率对偶犹豫模糊PROMETHEE多属性群决策算法

为解决犹豫模糊环境中由随机性和不确定性对实际决策造成偏差的多属性群决策问题,提出一种基于概率对偶犹豫模糊PROMETHEE的多属性群决策算法。构建各决策专家的概率对偶犹豫模糊信息矩阵;运用最大离差法与熵值法确定各决策专家与各指标属性的客观权重,结合改进的得分函数与偏离函数得到专家的综合决策评价信息矩阵;进而通过概率对偶犹豫模糊集与PROMETHEE结合的决策算法得到最终决策结果。将该算法运用于航空灾难事故应急响应方案评估的算例分析中,通过与TOPSIS、VIKOR及PDHFS决策算法的计算结果进行对比,验证了概率对偶犹豫模糊PROMETHEE多属性群决策算法的有效性与可靠性。     

基于模糊偏好关系的多智能主体决策

多智能主体决策在决策支持系统中的应用越来越广泛,但也带来了各智能主体决策一致性,以及选择最优决策方案的问题,为解决以上问题,该文提出了基于模糊偏好关系的多智能主体决策方法,该方法利用模糊聚合算子对多智能主体的决策结果进行聚合,并利用模糊偏好关系对决策方案进行排序,从而选择最优决策方案。     

模糊智能决策树模型与应用研究

决策问题是计算智能最核心的问题之一.基于模糊数学理论建立了一个普适的模糊决策树模型;用节点刻画决策前提和控制信息,用树上的边形式化推理规则;并在节点和边上定义合理的模糊决策算子,进行多级综合决策.工程决策考虑不同方案的成本、可行性和收益,将这些信息进行融合作为决策方案优劣的测度;建立加权模糊智能决策模型,并给出了基于该...     

基于多种偏好信息的物流方案评估方法

为了有效地反映物流方案评价中评价信息的模糊性,提出了基于多种偏好信息的物流方案评估方法。决策者采用各自偏好的信息形式对物流方案进行评价;利用转换函数将多种形式的偏好信息一致化为模糊互补判断矩阵,应用行和归一化方法计算排序向量,从而将决策成员的权重集结并获得物流方案的初始优先度;合成初始优先度与各项评价相应的修正系数,并通过规范化处理得到物流方案的优先度。通过一个实例验证所提方法。     

An integrated approach to machine selection problem using fuzzy SMART-fuzzy weighted axiomatic design

In respond to new market requirements and competitive positioning of manufacturing companies selecting optimal machines that are consistent with manufacturing goals is of crucial importance. As it involves multiple conflicting criteria and inherent ambiguity and vagueness, election of a suitable machine can be regarded as a fuzzy multi-criteria decision making problem. In this study, for the first time in the literature, an integrated approach consisting of fuzzy simple multiattribute rating technique (SMART) approach and fuzzy weighted axiomatic design (FWAD) approach is proposed to determining the optimal continuous fluid bed tea dryer for a privately owned tea plant operating in Turkey. The weights of the evaluation criteria are calculated via fuzzy SMART and then FWAD is utilized to rank competing machine alternatives in terms of their overall performance. In the FWAD application phase, five experts have determined functional requirements (FRs) and have rated alternatives. Therefore, individual fuzzy opinions were required to be aggregated in order to set up a group consensus. A group decision analysis, referred to as the least squares distance method is used to aggregating the ratings of FRs and alternatives. It is concluded that the proposed hybrid methodology is a robust decision support tool for ranking machine alternatives under fuzzy environment and furthermore, it can be exploited for other fuzzy decision making problems, as well.     

A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method

Supplier selection, the process of finding the right suppliers who are able to provide the buyer with the right quality products and/or services at the right price, at the right time and in the right quantities, is one of the most critical activities for establishing an effective supply chain. On the other hand, it is a hard problem since supplier selection is typically a multi criteria group decision-making problem involving several conflicting criteria on which decision maker’s knowledge is usually vague and imprecise. In this study, TOPSIS method combined with intuitionistic fuzzy set is proposed to select appropriate supplier in group decision making environment. Intuitionistic fuzzy weighted averaging (IFWA) operator is utilized to aggregate individual opinions of decision makers for rating the importance of criteria and alternatives. Finally, a numerical example for supplier selection is given to illustrate application of intuitionistic fuzzy TOPSIS method.     

A peer IF-TOPSIS based decision support system for packaging machine selection

Selecting the appropriate manufacturing machine is a very important and complex problem for firms which usually have to deal with both qualitative and quantitative criteria and involve different decision makers whose knowledge is often vague and imprecise.This paper proposes a peer-based modification to intuitionistic fuzzy multi-criteria group decision making with TOPSIS method (peer IF-TOPSIS) and applies it to a packaging machine selection problem. Intuitionistic fuzzy weighted averaging (IFWA) operator has been selected both to obtain the group opinion on the relevance of the single decision makers and to aggregate individual opinions of decision makers for rating the importance of criteria and alternatives.A case study illustrates the application of the modified IF-TOPSIS method in order to select a Vertical Form Fill and Seal (VFFS) for Double Square Bottom Bag (DSBB) machine in food packaging.     

Possibilistic programming approach for fuzzy multidimensional analysis of preference in group decision making

Multiple attribute decision making (MADM) problems are the most encountered problems in decision making. Fuzziness is inherent in decision making process and linguistic variables are well suited to assessing an alternative on qualitative attributes using fuzzy rating. A few techniques in MADM assess the weights of attributes based on preference information on alternatives. But they are not practical any more when the set of all paired comparison judgments from decision makers (DMs) on attributes are not crisp and also we have to deal with fuzzy decision matrix. This paper investigates the generation of a possibilistic model for multidimensional analysis of preference (LINMAP). The model assesses the fuzzy weights as well as locating the ideal solution with fuzzy decision making preference on attributes and fuzzy decision matrix. All of the information is assumed as triangular fuzzy numbers (TFNs). This method is developed in group decision making environments and formulates the problem as a possibilistic programming with multiple objectives.     

Novel intuitionistic fuzzy decision making models in the framework of decision field theory

The intuitionistic fuzzy decision making problems have gained great popularity recently. Most of the current methods depend on various aggregation operators that provide collective intuitionistic fuzzy values of alternatives to be ranked. Such collective information only depicts the overall characteristics of the alternatives but ignores the detailed contrasts among them. Most important of all, the current decision making procedure is not in accordance with the way that the decision makers (DMs) think about the decision making problems. In this paper, we develop a novel intuitionistic fuzzy decision making model in the framework of decision field theory. The decision making model emphasizes the contrasts among alternatives with respect to each attribute that competes and influences each other, and thus, the preferences for alternatives can dynamically evolve and provide the final optimal result. After that, we develop an intuitionistic fuzzy group decision making model based on decision field theory, and then make a practical case study on the application of the developed models to the “one belt, one road” investment decision making problems. Finally, we point out the characteristics and the limitations of our models in detail.     

Robot selection by using generalized interval-valued fuzzy numbers with TOPSIS

The aim of this paper is to propose a method to aggregate the opinion of several decision makers on different criteria, regarding a set of alternatives, where the judgment of the decision makers are represented by generalized interval-valued trapezoidal fuzzy numbers. A generalized interval valued trapezoidal fuzzy number based technique for order preference by similarity to ideal solution is proposed that can reflect subjective judgment and objective information in real life. The weights of criteria and performance rating values of criteria are linguistic variables expressed as generalized interval-valued trapezoidal fuzzy numbers. Finally, an illustrative example is provided to elaborate the proposed method for the selection of a suitable robot according to our requirements.     

A new linguistic MCDM method based on multiple-criterion data fusion

Multiple-criteria decision-making (MCDM) is concerned with the ranking of decision alternatives based on preference judgements made on decision alternatives over a number of criteria. First, taking advantage of data fusion technology to comprehensively consider each criterion data is a reasonable idea to solve the MCDM problem. Second, in order to efficiently handle uncertain information in the process of decision making, some well developed mathematical tools, such as fuzzy sets theory and Dempster Shafer theory of evidence, are used to deal with MCDM. Based on the two main reasons above, a new fuzzy evidential MCDM method under uncertain environments is proposed. The rating of the criteria and the importance weight of the criteria are given by experts’ judgments, represented by triangular fuzzy numbers. Then, the weights are transformed into discounting coefficients and the ratings are transformed into basic probability assignments. The final results can be obtained through the Dempster rule of combination in a simple and straight way. A numerical example to select plant location is used to illustrate the efficiency of the proposed method.     

FOWG算子在X射线检测方案选择中的应用

针对当前X射线数字化实时成像检测技术的广泛应用，研究了决策信息以三角模糊数互补判断矩阵形式给出的有限方案决策问题，给出了一种模糊有序加权平均（FOWA）算子，利用该算子对以三角模糊数互补判断矩阵形式给出的判断信息进行了集结。基于FOWG算子及互补判断矩阵排序公式，给出了一种对决策方案进行排序和择优的算法。利用该算法对长输管道钢质对接焊缝X射线数字化实时成像检测方案进行排序和择优，最后通过算例说明了该方法的有效性和实用性。     

An intuitionistic fuzzy group decision making method using entropy and association coefficient

Group decision making is a process in which experts rank and choose the most desirable alternatives based on some accepted criteria. The aim of this paper was to introduce a method to solve group decision making problems with Atanassov’s intuitionistic fuzzy sets. First, the weight of each criterion is calculated using intuitionistic fuzzy entropy. Then, the total criteria weight vector is calculated by aggregating the calculated weights. Using the obtained weight vector, the alternatives are ranked based on the association coefficient of the performance of alternatives related to each criterion and the positive ideal intuitionistic fuzzy set value and the negative ideal intuitionistic fuzzy set value. Finally, to show the application of the proposed method, it is implemented in software vendor selection.     

Extension of VIKOR method in intuitionistic fuzzy environment for robot selection

Decision making is the process of finding the best option among the feasible alternatives. In classical multiple-criteria decision making methods, the ratings and the weights of the criteria are known precisely. However, if decision makers are not able to involve uncertainty in the defining of linguistic variables based on fuzzy sets, the intuitionistic fuzzy set theory can do this job very well. In this paper, VIKOR method is extended in intuitionistic fuzzy environment, aiming at solving multiple-criteria decision making problems in which the weights of criteria and ratings of alternatives are taken as triangular intuitionistic fuzzy set. For application and verification, this study presents a robot selection problem for material handling task to verify our proposed method.