Use of multi-attribute decision analysis for designing operations system framework in telecommunications management network

This paper is concerned with the design of an Operations System (OS) framework for implementing a proper telecommunications network in Korea Telecom. Since several types of OS frameworks are under consideration, the telecommunication network manager should now choose the best alternative for use later in establishing the infrastructure of operations systems. The decision making is done in this paper by means of a Multi-Attribute Decision-Making (MADM) analysis. A point to be noted in the present case is that the decision relevant information such as attribute weights and values of alternatives are not known exactly. Rather, these are to be taken in the form of rankings and/or bounds. To deal with such incomplete information, we employ a mathematical programming model-based MADM approach to the choice of an optimal OS framework design. This approach enables us to check dominance of alternatives and to obtain a set of non-dominated alternatives from evaluating five alternatives in reference to Telecommunications Management Network (TMN) standards.

Scope and purpose

Telecommunications Management Network (TMN) can be stated as a globalized and unified skeleton to meet the advanced operational environments of telecommunications networks and to handle heterogeneous and complex network elements. Although there are various subjects that should be addressed to accomplish TMN, we confine our attention to dealing with one important subject, design of an Operations System (OS) framework. This is necessary to manage telecommunications resources including networks in effective manner and for use as guidance in developing individual operations systems and in constructing a network management center.Several types of OS frameworks have been suggested by TMN standards. It is hence needed to evaluate each of these OS frameworks and then to choose an appropriate one in Korean TMN situation. Since this evaluation involves multiple criteria (or attributes), it is realized in this paper by a Multi-Attribute Decision-Making (MADM) analysis approach. The decision relevant information such as trade-off weights and individual criterion values are elicited from expert opinions which, however, is rather incomplete than exact numerical values. The decision making process with the incompletely identified information is presented in this paper.     

Sustainable market valuation of buildings by the single-valued neutrosophic MAMVA method

Traditionally, the real estate asset assessment is performed by experienced valuators, who take into account its economic, social, physical and locational aspects. Nowadays, the construction industry is becoming more and more influenced by the sustainability requirements. Therefore, the inclusion of the sustainability evaluation into real estate asset valuation is of utmost importance. The Neutrosophic Multi-Attribute Market Value Assessment (MAMVA) method developed by the authors of this article handles market value calculations by solving multiple criteria assessment problems, and the initial information vagueness is modelled explicitly. The supplementary novelty of the present paper is the inclusion of the sustainability aspects into the real estate market valuation. The sustainable market valuation of Croydon University Hospital (Emergency Department) is performed as the case study to present numerical capabilities of the proposed approach. Our research findings suggest that neutrosophic MAMVA is a rational approach for calculations of property market valuation and might be suitable for application worldwide.     

直觉模糊信息环境下考虑后悔规避的决策方法

针对属性值为直觉模糊信息、属性权重和自然状态发生概率完全未知的多属性决策问题,考虑决策者的心理行为,提出一种基于后悔理论和证据理论的多属性决策方法。该方法首先运用证据理论计算各自然状态发生的概率;然后基于得到的区间模糊矩阵、[t-]分布估计以及得分函数矩阵确定属性信息的效用值,进而依据后悔理论得到各种自然状态下的感知效用矩阵;通过加权算术平均计算综合感知效用矩阵,并依据方案综合感知效用的大小确定方案优劣排序。通过对游戏的选择开发实例验证提出的决策方法的可行性与有效性。     

Pythagorean犹豫模糊灰色关联前景多属性决策方法

针对Pythagorean犹豫模糊环境下的多属性决策问题,提出了一种基于前景理论的Pythagorean犹豫模糊灰色关联多属性决策方法。定义了Pythagorean犹豫模糊数的灰色关联度和前景价值函数。基于灰色关联度定义了各方案相对于正负理想解的差异集,结合前景价值函数将Pythagorean犹豫模糊决策矩阵转化为价值矩阵。通过各方案的收益损失比值对备选方案进行优劣排序。为了说明该决策方法的可行性和有效性,将其应用到能源项目的综合评价上,并通过实例对比验证了提出决策方法的优越性。     

三角模糊数在多属性决策中的建模

为了获得三角模糊数的多属性决策数学模型,将语言变量和三角模糊数引入到多属性决策中,用语言变量或三角模糊数表示多属性决策中的属性值和各属性的权重,采用加权和法求得每个备选方案的三角模糊数最终评价值,并应用三角模糊数的减法运算定义任意两个三角模糊数的优越度,在方案两两对比求得优越度后建立方案的互补判断矩阵,采用最小平方法求得方案排序向量,根据排序向量元素的大小进行方案排序。     

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。     

单值中智信息熵及其多属性决策方法

针对评估信息为单值中智数的多属性决策问题,建立了基于单值中智熵的多属性决策方法。首先,针对现有单值中智熵定义的不足,引入了新的单值中智熵的公理化定义;其次,基于三角函数,设计了一种衡量单值中智数不确定性的信息熵公式,并证明其满足单值中智熵的四个公理化条件;然后,运用提出的熵公式,并结合Lagrange乘数法和贴近度,构建了一种新的单值中智多属性决策方法;最后,将提出的决策方法运用于数据产品服务商的选择问题验证该方法的合理性与有效性。     

Bidirectional project method for dual hesitant Pythagorean fuzzy multiple attribute decision-making and their application to performance assessment of new rural construction

The dual hesitant Pythagorean fuzzy set (DHPFS) consists of two parts, that is, the membership hesitancy function and the nonmembership hesitancy function, supporting a more exemplary and flexible access to assign values for each element in the domain. It is very suitable to handle the situation that there are various possible values in membership and nonmembership degrees to depict the true circumstance. The bidirectional project method of DHPFS calculates method considered not only the bidirectional projection magnitudes and the distance but also includes angle between objects evaluated. Therefore, this paper proposes a bidirectional project method of DHPFS to handle the multiple attribute decision-making (MADM) problem under the dual hesitant Pythagorean fuzzy environment. Through the measure between each alternative decision matrix and the positive and negative ideal alternative matrix, the ranking order all alternatives can be used to select the best alternative. Furthermore, a model for MADM has been given. Finally, a numerical example for performance assessment of new rural construction has been given to demonstrate the application of bidirectional project method of DHPFS, and we used the dual hesitant Pythagorean weighted Bonferroni mean to compare its reasonable and effectiveness.     

Evaluation of multi-attribute decision making systems applied during the concept design of new microplasma devices

Various multi-attribute decision making (MADM) systems can be implemented to narrow a field of new concept designs down to those with high likelihoods of surpassing state-of-the-art technologies. This research investigated the conceptual design phase of new microplasma devices in order to create metrics that evaluate the efficiency, effectiveness, and overall utility of representative MADM systems studied in previous engineering design applications. Device attributes and concept alternatives for the microplasma devices were identified from open-ended expert surveys. Efficiency metrics were defined based on the number of manual user inputs. Published device literature and testing were used to gauge how closely device concepts satisfied multi-attribute criteria, forming the basis of an effectiveness metric. A weighted average of the efficiency and effectiveness defined a MADM system’s overall utility. Varying the effectiveness weight provided further insight into the conditions under which particular MADM approaches exhibited higher utility values. The MADM systems found to possess the highest overall quantified utilities were based on Pugh’s controlled convergence, Utility Based Axiomatic Framework, and Grey Relational Analysis. The MADM method with the lowest overall utility was the analytical hierarchy process. These findings indicate that consensus building and utility-based MADM systems are especially helpful to engineering design teams during the early design phases of novel technologies when resources are constrained or historical data is limited.     

Multiperiod multiattribute decision‐making method based on trend incentive coefficient

In this paper, we develop a method for multiperiod multiattribute decision‐making (MP‐MADM) problems, in which the decision information, including attribute weights and attribute values, is given at different periods. First, using the variation in attribute values of the various alternatives for unit time, we can obtain the trend incentive coefficient of variation that represents reward or punishment for the development tendency of alternatives. This paper proposes a method based on maximum entropy ordered weighted averaging (MEOWA) to determine the trend incentive coefficient. Second, considering the differences development tendency of the alternatives, we propose an approach that integrates the trend incentive coefficient and the original decision information to solve the MP‐MADM problems. Finally, two MP‐MADM cases are used to illustrate the effectiveness and practicability of the proposed method. Comparisons with previous research are also discussed.     

基于分布式偏好关系的多属性决策方法及运用*

针对利用分布式偏好关系建模且考虑其一致性的多属性决策问题,提出了一种满足一致性的多属性决策方法。给定相邻方案间的分布式偏好关系,首先构建了基于等级得分值的等级合成规则并分析其性质,而后基于等级合成规则定义了分布式偏好关系矩阵的一致性判定准则,进而提出满足一致性的不同方案对间分布式偏好关系合成规则,最后以此规则为核心,设计多属性决策方法的流程,产生了满足一致性的决策结果。将提出的方法应用于芜湖市战略性新兴产业评估,验证了方法的应用性和有效性。     

基于犹豫语言决策模型的数据产品服务商选择

针对属性值为犹豫模糊语言元的多属性决策问题,建立基于犹豫模糊语言可能度的线性分配决策模型。首先,基于犹豫模糊语言元的包络转化方法,分别定义了犹豫模糊语言元间的可能度和相对差异指数等概念;其次探究发现可能度矩阵和相对差异矩阵均为互补判断矩阵,并设计了犹豫模糊语言元的最优度计算公式;最后,在犹豫模糊语言信息环境下,构建了一种新的线性分配决策模型用以确定各备选方案的综合最优度,进而遴选出最优方案。实验结果表明,提出的决策模型是可行和有效的。     

基于犹豫模糊H-平均的交通流模型选择方法

针对输入变量之间存在相互影响和联系以及属性值为犹豫模糊信息的多属性决策问题,基于阿基米德范数和Heronian平均,提出一种新的犹豫模糊Heronian平均（HFHM）算子;详细研究了HFHM算子的一些基本性质,包括幂等性、单调性和有界性;探讨了HFHM算子的一些特例,并提出了犹豫模糊加权Heronian平均（HFWHM）算子;进一步,基于HFWHM算子建立了一种新的犹豫模糊多属性决策方法,该决策方法不仅能够有效地捕获输入变量之间的相互联系,还使得决策者能够依据自身的风险偏好态度选择不同的参数进行决策。最后,通过交通流模型的选择实例对提出的决策方法进行了有效性验证。     

基于可能度矩阵的区间型多属性决策方法

研究了几组可能度公式之间的关系,提出一种基于可能度矩阵的区间型多属性决策(MADM)方法。对决策矩阵中各指标下的属性区间值两两比较并建立各指标的可能度矩阵,通过各个可能度矩阵的排序向量把属性值为区间数的决策矩阵转化为以精确数为测度的矩阵,把求解区间型多属性决策中指标权重的不确定性问题转化为确定性问题处理,随后利用区间数排序的可能度法获得最优方案。实验结果表明了所提方法的可行性和有效性。最后对多属性决策问题中由不确定性转化为确定性的求解策略及其可能产生的问题作了必要讨论。     

Fuzzy linear programming approach to multiattribute decision making with multiple types of attribute values and incomplete weight information

In the classical Linear Programming Technique for Multidimensional Analysis of Preference (LINMAP), the decision maker (DM) gives the pair-wise comparisons of alternatives with crisp truth degree 0 or 1. However, in the real world, DM is not sure enough in all comparisons and can express his/her opinion with some fuzzy truth degree. Thus, DM's preferences are given through pair-wise comparisons of alternatives with fuzzy truth degrees, which may be represented as trapezoidal fuzzy numbers (TrFNs). Considered such fuzzy truth degrees, the aim of this paper is to develop a new fuzzy linear programming technique for solving multiattribute decision making (MADM) problems with multiple types of attribute values and incomplete weight information. In this method, TrFNs, real numbers, and intervals are used to represent the multiple types of decision information. The fuzzy consistency and inconsistency indices are defined as TrFNs due to the alternatives’ comparisons with fuzzy truth degrees. Hereby a new fuzzy linear programming model is constructed and solved by the possibility linear programming method with TrFNs developed in this paper. The fuzzy ideal solution (IS) and the attribute weights are then obtained. The distances of alternatives from the fuzzy IS can be calculated to determine their ranking order. The implementation process of the method proposed in this paper is illustrated with a strategy partner selection example. The comparison analyzes show that the method proposed in this paper generalizes the classical LINMAP, fuzzy LINMAP and possibility LINMAP.     

Fuzzy heterogeneous multiattribute decision making method for outsourcing provider selection

One of the critical activities for outsourcing success is outsourcing provider selection, which may be regarded as a type of fuzzy heterogeneous multiattribute decision making (MADM) problems with fuzzy truth degrees and incomplete weight information. The aim of this paper is to develop a new fuzzy linear programming method for solving such MADM problems. In this method, the decision maker’s preferences are given through pair-wise alternatives’ comparisons with fuzzy truth degrees, which are expressed with trapezoidal fuzzy numbers (TrFNs). Real numbers, intervals, and TrFNs are used to express heterogeneous decision information. Giving the fuzzy positive and negative ideal solutions, we define TrFN-type fuzzy consistency and inconsistency indices based on the concept of the relative closeness degrees. The attribute weights are estimated through constructing a new fuzzy linear programming model, which is solved by using the developed fuzzy linear programming method with TrFNs. The relative closeness degrees of alternatives can be calculated to generate their ranking order. An example of the IT outsourcing provider selection problem is analyzed to demonstrate the implementation process and applicability of the method proposed in this paper.     

A novel risk attitudinal ranking method for intuitionistic fuzzy values and application to MADM

The ranking of intuitionistic fuzzy sets (IFSs) is very important for the intuitionistic fuzzy decision making. The aim of this paper is to propose a new risk attitudinal ranking method of IFSs and apply to multi-attribute decision making (MADM) with incomplete weight information. Motivated by technique for order preference by similarity to ideal solution (TOPSIS), we utilize the closeness degree to characterize the amount of information according to the geometrical representation of an IFS. The area of triangle is calculated to measure the reliability of information. It is proved that the closeness degree and the triangle area just form an interval. Thereby, a new lexicographical method is proposed based on the intervals for ranking the intuitionistic fuzzy values (IFVs). Furthermore, considered the risk attitude of decision maker sufficiently, a novel risk attitudinal ranking measure is developed to rank the IFVs on the basis of the continuous ordered weighted average (C-OWA) operator and this interval. Through maximizing the closeness degrees of alternatives, we construct a multi-objective fractional programming model which is transformed into a linear program. Thus, the attribute weights are derived objectively by solving this linear program. Then, a new method is put forward for MADM with IFVs and incomplete weight information. Finally, an example analysis of a teacher selection is given to verify the effectiveness and practicability of the proposed method.     

A mathematical programming approach to multi-attribute decision making with interval-valued intuitionistic fuzzy assessment information

This article proposes an approach to handle multi-attribute decision making (MADM) problems under the interval-valued intuitionistic fuzzy environment, in which both assessments of alternatives on attributes (hereafter, referred to as attribute values) and attribute weights are provided as interval-valued intuitionistic fuzzy numbers (IVIFNs). The notion of relative closeness is extended to interval values to accommodate IVIFN decision data, and fractional programming models are developed based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to determine a relative closeness interval where attribute weights are independently determined for each alternative. By employing a series of optimization models, a quadratic program is established for obtaining a unified attribute weight vector, whereby the individual IVIFN attribute values are aggregated into relative closeness intervals to the ideal solution for final ranking. An illustrative supplier selection problem is employed to demonstrate how to apply the proposed procedure.     

A Problem-based Selection of Multi-attribute Decision-making Methods

Different multi-attribute decision-making (MADM) methods often produce different outcomes for selecting or ranking a set of decision alternatives involving multiple attributes. This paper presents a new approach to the selection of compensatory MADM methods for a specific cardinal ranking problem via sensitivity analysis of attribute weights. In line with the context-dependent concept of informational importance, the approach examines the consistency degree between the relative degree of sensitivity of individual attributes using an MADM method and the relative degree of influence of the corresponding attributes indicated by Shannon's entropy concept. The approach favors the method that has the highest consistency degree as it best reflects the decision information embedded in the problem data set. An empirical study of a scholarship student selection problem is used to illustrate how the approach can validate the ranking outcome produced by different MADM methods. The empirical study shows that different problem data sets may result in a different method being selected. This approach is particularly applicable to large-scale cardinal ranking problems where the ranking outcome of different methods differs significantly.     

犹豫模糊语言环境下的无线传感器选择方法

无线传感器系统的选择是无线传感器管理中的一个重要课题,其本质是一个多属性决策问题。针对犹豫模糊语言环境下无线传感器的选择问题,基于前景理论和证据理论的思想,提出一种新的犹豫模糊语言多属性决策方法。该决策方法首先利用证据理论确定各自然状态发生的概率,进而得到每种状态发生的决策权重函数;其次,运用正态分布概率密度函数构建犹豫模糊语言决策参考点,并基于属性值与决策参考点之间的距离计算价值函数矩阵,从而获得前景价值矩阵;进一步构建以综合前景价值最大化为目标函数的最优化模型求解属性权重,并依据各无线传感器系统的综合前景价值进行优劣排序。通过对无线传感器系统的选择实例验证提出的决策方法的可行性与有效性。