Extension of TOPSIS for fuzzy multi-attribute decision making problem based on experimental analysis

This paper is concerned with a technique for order performance by similarity to ideal solution（TOPSIS） method for fuzzy multi-attribute decision making,in which the information about attribute weights is partly known and the attribute values take form of triangular fuzzy numbers.Considering the fact that the triangular fuzzy TOPSIS results yielded by different distance measures are different from others,a comparative analysis of triangular fuzzy TOPSIS ranking from each distance measure is illustrated with discussion on standard deviation.By applying the most reasonable distance,the deviation degrees between attribute values are measured.A linear programming model based on the maximal deviation of weighted attribute values is established to obtain the attribute weights.Therefore,alternatives are ranked by using TOPSIS method.Finally,a numerical example is given to show the feasibility and effectiveness of the method.

Multi-attributed decision making for mining methods based on grey system and interval numbers

In the case of unknown weights, theories of multi-attributed decision making based on interval numbers and grey related analysis were used to optimize mining methods. As the representative of independence for the indicator, the smaller the correlation of indicators is, the greater the weight is. Hence, the weights of interval numbers of indicators were determined by using correlation coefficient. Relative closeness based on positive and negative ideal methods was calculated by introducing distance between interval numbers, which made decision making more rational and comprehensive. A new method of ranking interval numbers based on normal distribution was proposed for the optimization of mining methods, whose basic properties were discussed. Finally, the feasibility and effectiveness of this method were verified by theories and practice.

Application of TOPSIS Method in Support of Decisions Made in Staff Management Issues

Evaluation model was proposed which refers to fuzzy formalism of the personnel management issues taking account their specific characteristics. Application of TOPSIS （technique for order Performance by similarity to ideal solution） method for evaluation and regulation of alternatives based on hierarchically structured criteria of qualitative character by multiple experts to intellectually support decisions made in staff management issues is reviewed in the article. Candidate selection experiment based on criteria system formed using TOPSIS method for evaluation of candidates during solution of hiring problems reviewed and obtained results were compared with results obtained using Matlab program package.

Application of an Optimized Entropy-TOPSIS Multicriteria Decision Making Model to Facilities Management

Performance evaluation of facilities management plays a key role in the facilities management process. This paper proposes an optimized multicriteria decision making model to evaluate the performance of facilities management in schools in Hong Kong. In this model, entropy weights acted as weight coefficients for evaluated criteria in order to avoid uncertainty and randomicity of subjective judgments. Besides, the TOPSIS method was incorporated in this model. Then this model was em- ployed to evaluate the performance of facilities management in classrooms, offices and laboratories and satisfying results were obtained. Moreover, findings indicated that one of the schools could be rehabilitated rather than removed.

Improved TOPSIS decision model for NPP emergencies

In this paper,an improved decision model is developed for its use as a tool to respond to emergencies at nuclear power plants.Given the complexity of multi-attribute emergency decision-making on nuclear accident,the improved TOPSIS method is used to build a decision-making model that integrates subjective weight and objective weight of each evaluation index.A comparison between the results of this new model and two traditional methods of fuzzy hierarchy analysis method and weighted analysis method demonstrates that the improved TOPSIS model has a better evaluation effect.

Using Mathematical Models in Decision Making Methodologies to Find Key Nodes in the Noordin Dark Network

A Dark Network is a network that cannot be accessed through tradition means. Once uncovered, to any degree, dark network analysis can be accomplished using the SNA software. The output of SNA software includes many measures and metrics. For each of these measures and metric, the output in ORA additionally provides the ability to obtain a rank ordering of the nodes in terms of these measures. We might use this information in decision making concerning best methods to disrupt or deceive a given dark network. In the Noordin Dark network, different nodes were identified as key nodes based upon the metric used. Our goal in this paper is to use methodologies to identify the key players or nodes in a Dark Network in a similar manner as we previously proposed in social networks. We apply two multi-attribute decision making methods, a hybrid AHP & TOPSIS and an average weighted ranks scheme, to analyze these outputs to find the most influential nodes as a function of the decision makers’ inputs. We compare these methods by illustration using the Noordin Dark Network with seventy-nine nodes. We discuss sensitivity analysis that is applied to the criteria weights in order to measure the change in the ranking of the nodes.

改进TOPSIS的多属性决策方法

针对逼近理想点排序法(technique for order preference by similarity to ideal solution,TOPSIS)存在的缺陷,提出基于Tanimoto系数和基于对称差的2种改进TOPSIS。改善或解决TOPSIS存在指标相关性问题、特殊样本集合无法比较优劣问题和样本数据动态变化时产生的逆序现象等缺陷;在稳定性、特异性、敏感性和有效性4方面对经典TOPSIS模型、改进Tanimoto模型和改进对称差模型进行对比验证,给出2种改进模型的适用场景。结果表明,2种方法各具有一定的优势。

Alunite processing method selection using the AHP and TOPSIS approaches under fuzzy environment

Alunite is the most important non bauxite resource for alumina. Various methods have been proposed and patented for processing alunite, but none has been performed at industrial scale and no technical,operational and economic data is available to evaluate methods. In addition, selecting the right approach for alunite beneficiation, requires introducing a wide range of criteria and careful analysis of alternatives.In this research, after studying the existing processes, 13 methods were considered and evaluated by 14 technical, economic and environmental analyzing criteria. Due to multiplicity of processing methods and attributes, in this paper, Multi Attribute Decision Making methods were employed to examine the appropriateness of choices. The Delphi Analytical Hierarchy Process(DAHP) was used for weighting selection criteria and Fuzzy TOPSIS approach was used to determine the most profitable candidates. Among 13 studied methods, Spanish, Svoronos and Hazan methods were respectively recognized to be the best choices.

基于组合赋权-TOPSIS法的拆卸方案决策研究

拆卸是回收和再制造的重要步骤,为了使拆卸方案达到高效率、低排放以及高经济效益的目标,文章建立一种基于组合赋权-TOPSIS(technique for order preference by similarity to an ideal solution)法的拆卸方案决策模型。针对拆卸方案,从环境、技术和经济3个角度构建拆卸方案评价指标体系;依据最小信息熵原理,综合改进层次分析法(analytic hierarchy process,AHP)、熵权法与CRITIC(criteria importance through intercriteria correlation)法,为各指标进行组合赋权;使用组合权重改进TOPSIS模型,构建拆卸方案的贴近度指标,对拆卸方案进行判定;以银行自动取款机(automated teller machine,ATM)拆卸为实例进行分析,并与其他决策模型对比,验证所提决策模型的合理性及有效性,实现多拆卸方案的决策。

基于区间模糊DEMATEL和TOPSIS法的产品方案评价

针对目前产品方案评价方法存在的不足,提出一种基于区间模糊理论的多属性决策模型,该模型结合DEMATEL法和TOPSIS算法,采用区间模糊理论表达信息的不确定性:由DEMATEL方法对产品方案评价系统中的评价指标进行量化分析,对指标集进行因果分类、重要度排序和权重分配;在TOPSIS框架下构建区间模糊矩阵,计算其正、负理想解和接近度,根据接近度对产品备选方案进行比较,并进行了实例分析。结果表明,该评价方法和理论具有一定的实用性和可行性。

基于广义正交三角模糊数的WSM-TOPSIS群决策方法

结合广义正交模糊集和三角直觉模糊数,给出广义正交三角模糊数的定义和运算法则,在此基础上,对WSM和TOPSIS方法进行拓展,提出一种多属性群决策方法WSM-TOPSIS。考虑到决策者和属性的权重,该方法使用WSM对决策者提出的决策矩阵进行第一次集结,通过TOPSIS计算各方案的相对贴近度得到方案的优劣排序。最后通过实例和对比分析验证了该方法的有效性和实用性。

基于前景理论和TOPSIS的数字资源服务绩效研究

依据前景理论和TOPSIS法,深入探究数字资源服务绩效的特征,试图深入揭示用户决策行为规律,为一流学科数字资源建设提供理论指导与方法支持。参考相关研究成果,构建了数字资源绩效评价指标体系,设计基于前景理论和TOPSIS方法的数字资源服务绩效评价方法,并使用6个数字资源的数据进行应用研究。与传统TOPSIS方法相比,在保证评价稳定性的同时,验证了在不同参数、不同参考点及不同权重函数条件下,实际决策行为中人们的风险偏好和风险厌恶。

基于LAHP-TOPSIS方法的围填海方案选择研究

针对围填海不同规模方案的选择问题,目前已有很多文献建立了评价指标体系,然而利用数学算法进行评价研究的还比较少。文章以现存的评价指标体系和专家评分为基础,利用语言层次分析法(LAHP)来计算各个评价指标的权重,并采用多属性决策方法——逼近理想点法(TOPSIS)对不同规模的围填海方案进行排序,从而选出最优方案。进一步用实际的例子,说明了利用LAHP-TOPSIS方法进行方案排序的步骤,给出了评价结果。结果显示:文章提出的评价方法能够为沿海及港口城市围填海方案提供有效的评价工具,对于围填海规模方案选择具有重要意义。

基于直觉模糊GRA-TOPSIS的突击航线评估

为给指挥员提供更理想的突击航线选择方案,提出了一种基于直觉模糊GRA-TOPSIS的多属性决策方法。首先分析构建出贴合作战实际的突击航线评估指标体系,然后利用直觉模糊集理论的直觉模糊加权平均算子对决策专家评估矩阵进行集结,并利用直觉模糊交叉熵计算属性权重,之后使用GRA-TOPSIS模型对待选突击航线进行择优排序,最后通过实例计算和对比分析验证所提方法的有效性和可靠性,为突击航线评估提供了一种新方法。

Mathematical Modeling in Social Network Analysis： Using TOPSIS to Find Node Influences in a Social Network

In a social network analysis the output provided includes many measures and metrics. For each of these measures and metric, the output provides the ability to obtain a rank ordering of the nodes in terms of these measures. We might use this information in decision making concerning disrupting or deceiving a given network. All is fine when all the measures indicate the same node as the key or influential node. What happens when the measures indicate different key nodes？ Our goal in this paper is to explore two methodologies to identify the key players or nodes in a given network. We apply TOPSIS to analyze these outputs to find the most influential nodes as a function of the decision makers＇ inputs as a process to consider both subjective and objectives inputs through pairwise comparison matrices. We illustrate our results using two common networks from the literature： the Kite network and the Information flow network from Knoke and Wood. We discuss some basic sensitivity analysis can may be applied to the methods. We find the use of TOPSIS as a flexible method to weight the criterion based upon the decision makers＇ inputs or the topology of the network.

TOPSIS偏序法

对多属性决策中的TOPSIS法提出一种改进方法 ,使之可用来产生备选方案的偏序 ,而不是传统的全序结果 .阐述了这种改进方法的合理性 .将TOPSIS法及改进方法编写成了方便使用的MATLAB程序 .

一种基于前景理论和改进TOPSIS的模糊随机多准则决策方法及其应用

针对准则值为区间灰数直觉模糊数、准则权系数部分已知以及自然状态出现概率为灰数的多准则决策问题,提出一种结合前景理论和改进TOPSIS的决策方法。该方法首先定义了灰色直觉模糊数的前景价值函数和概率权重函数,并利用前景理论构建出前景决策矩阵;接着从两个方面对传统TOPSIS决策方法进行改进:(1)过定义方案间综合差异的概念,采用离差最大化思想,建立平均综合差异最大化规划模型,给出了一种兼顾主客观权重信息确定准则权系数的新方法;(2)用灰关联替换备选方案与正负理想方案的距离,据此刻画了各方案与正负理想方案的贴近度。进而利用改进TOPSIS决策方法中的综合贴近度对方案进行了排序。最后通过实例验证了该方法的有效性。

基于加权广义马氏距离的TOPSIS方法在水库防洪调度决策中的应用

针对汛期水库防洪调度决策指标存在相关性的特点以及基于欧氏距离的传统TOPSIS方法无法解决属性指标间相关性的不足,提出加权广义马氏距离计算公式,改进了TOPSIS方法,有效解决了属性指标之间的相关性、决策者主观偏好和决策信息客观属性对决策结果的影响以及协方差矩阵不可逆的问题.实例分析表明,该方法计算结果更符合工程实际,可为水库优选调度方案提供理论支撑.

一种基于联系度的改进TOPSIS法

提出了一种改进的TOPSIS决策方法。该方法将理想点与负理想点视为确定不确定系统中相互对立的集合,在考察目标方案与理想点或负理想点的联系度时,充分考虑了对立集合的存在;并通过引入联系向量距离的概念,计算相对贴近度,从而在一定程度上克服了传统TOPSIS法的不足。应用实例证明了该方法的可行性和有效性。

直觉模糊多属性决策的TOPSIS法

属性值和权重都是直觉模糊集的多属性决策问题不同于一般的多属性决策问题,不能运用现有的决策方法求解。本文给出了直觉模糊正、负理想方案的定义及其与每个方案的欧氏距离,进而建立了每个方案与直觉模糊正理想方案的相对贴近度计算方法,从此产生所有方案的优序排序,即拓展了TOPSIS法。数值实例说明了该方法的有效性和实用性,可为解决直觉模糊多属性决策提供新途径。