Extension of the TOPSIS method for decision making problems under interval-valued intuitionistic fuzzy environment

TOPSIS is one of the well-known methods for multiple attribute decision making (MADM). In this paper, we extend the TOPSIS method to solve multiple attribute group decision making (MAGDM) problems in interval-valued intuitionistic fuzzy environment in which all the preference information provided by the decision-makers is presented as interval-valued intuitionistic fuzzy decision matrices where each of the elements is characterized by interval-valued intuitionistic fuzzy number (IVIFNs), and the information about attribute weights is partially known. First, we use the interval-valued intuitionistic fuzzy hybrid geometric (IIFHG) operator to aggregate all individual interval-valued intuitionistic fuzzy decision matrices provided by the decision-makers into the collective interval-valued intuitionistic fuzzy decision matrix, and then we use the score function to calculate the score of each attribute value and construct the score matrix of the collective interval-valued intuitionistic fuzzy decision matrix. From the score matrix and the given attribute weight information, we establish an optimization model to determine the weights of attributes, and construct the weighted collective interval-valued intuitionistic fuzzy decision matrix, and then determine the interval-valued intuitionistic positive-ideal solution and interval-valued intuitionistic negative-ideal solution. Based on different distance definitions, we calculate the relative closeness of each alternative to the interval-valued intuitionistic positive-ideal solution and rank the alternatives according to the relative closeness to the interval-valued intuitionistic positive-ideal solution and select the most desirable one(s). Finally, an example is used to illustrate the applicability of the proposed approach.     

基于空间视角下产业协同集聚对区域创新的影响

选取2009-2018年中国30个省(市、自治区)的数据,运用区位商相对差异指数和熵权TOPSIS法分别测算其产业协同集聚度和区域创新水平,研究二三产业协同集聚对区域创新的影响.研究表明:产业集聚通过"知识技术、劳动力、物力"等外部规模经济增加创新产出;2009-2018年,两产业协同集聚水平由中西部向东部递减,区域创新水平东部明显高于中西部,空间溢出效应显著;两产业协同集聚对创新的影响呈现"倒U型"特征;最后基于计量结果提出相关建议.     

Incremental analysis for MCDM with an application to group TOPSIS

The study aims to exploit incremental analysis or marginal analysis to overcome the drawbacks of ratio scales utilized in various multi-criteria or multi-attribute decision making (MCDM/MADM) techniques. In the proposed 11-step procedure, multiple criteria of alternatives are first reorganized as two categories – benefits and costs – and decision information will be manipulated separately. The performances of alternatives are then evaluated on their incremental benefit–cost ratio, and the rank can be obtained by applying the group TOPSIS (technique for order preference by similarity to ideal solution) model (Shih et al., 2007). Two representations of cost, i.e., a cost index and utility index, are proposed in the model to better-fit real-world situations. In addition, some considerations on costs and input–output relations are also discussed in order to understand the essentials of incremental analysis. In the final part, a case of robot selection demonstrates the suggested model to be both robust and efficient in a group decision-making environment.     

巫山县乡村地区公路网通达性空间格局研究

以巫山县为研究区域,运用GIS技术,以乡镇和行政村为节点单元,采用公路网密度、乡镇间直达性指数、乡镇内直达性指数、居民点道路临近性、乡镇间节点可达性指数、乡镇内节点可达性指数、干线衔接距离、地形位指数8项指标,引入熵权-TOPSIS模型,综合分析和评价巫山县乡村地区公路网通达性及其空间分布格局。研究表明,各项指标对巫山县乡村公路网的影响程度由高到低为：公路网密度＞地形位指数＞干线衔接距离＞居民点临近性＞乡镇内直达性指数＞乡镇间节点可达性指数＞乡镇内节点可达性指数＞乡镇间直达性指数;除中心城区外,各乡镇贴近度为0.170 0＞0.831 9,区域差异明显,其中铜鼓最高,当阳最低;整体上,巫山县乡村公路通达性以中等、较好等级为主,通达性空间格局总体以铜鼓、建平、三溪为核往外围扩散,与交通干线骨架吻合度较高,呈现“三核、一环、一域”的空间格局。研究成果对巫山县山区乡村公路网建设和优化有一定的指导作用,在一定程度上完善了乡村地区公路网通达性分析和评价方法。     

一种基于TOPSIS法的单值中智多属性决策新方法

单值中智集(SVNS)是中智集(NS)的一种特殊情况,它可以描述现实世界中大量存在的不精确、不确定和不一致信息。由于语言评价的模糊性,传统的模糊评价方法在解决多属性决策(MADM)问题上效果不佳。针对这种情况,提出了一种基于TOPSIS法的单值中智多属性决策新方法。首先介绍了中智集的一些基本概念和运算规则,给出了两个单值中智集之间的广义距离公式;然后构建了聚合专家权重的单值中智决策矩阵,把TOPSIS法推广到单值中智集的环境下;接着通过偏好排序确定了最佳的决策方案。最后通过一个仿真实例,说明了该方案的有效和实用性。     

基于广义WOWA算子的Pythagorean模糊决策方法

针对Pythagorean模糊信息的决策问题,构建广义Pythagorean模糊信息加权有序加权平均(PF-GWOWA)算子。首先,提出PF-GWOWA算子,并证明Pythagorean模糊广义加权平均(PF-GWA)算子、Pythagorean模糊加权有序加权平均(PF-WOWA)算子与Pythagorean模糊加权平均(PF-WA)算子均为PF-GWOWA算子的特例;其次,根据GWOWA算子属性综合权重计算模型,利用PF-GWOWA算子对信息进行集结;最后,通过算例分析和传统方法对比,说明本文提出方法的合理性与有效性。     

一种动态评价法在钢铁企业低碳竞争力评价中的应用

在企业竞争力评价过程中,经常会遇到周期性、偶然性等问题,为解决这类问题,笔者在综合前人所提出“拉开档次”这一研究思路的基础上对TOPSIS法进行了拓展,并采用该方法对我国部分钢铁企业低碳竞争力进行了评价。研究结果表明,相对于现行的静态评价法,该法具有动态性、灵活性、综合性等优点,可以从各种角度反映钢铁企业的低碳竞争力状况。实证研究既验证了本方法的实用性和有效性,又解决了评价周期内巨大变化影响评价结论的问题,为企业低碳竞争力动态评价的研究提出了一种新的拓展思路。     

基于区间值直觉模糊集的TOPSIS多属性决策

基于区间值直觉模糊集,提出了一种新的TOPSIS模糊多属性决策方法。首先介绍区间直觉模糊集的概念,定义了两个区间值直觉模糊集之间的距离;然后根据TOPSIS方法的原理,定义了两个区间值直觉模糊集的接近系数,通过计算备选方案到区间值直觉模糊正理想解和负理想解的距离来确定接近系数,从而判断备选方案的优劣次序。最后,通过一个具体实例来说明这种方法的有效性和具体计算过程。     

一种基于TOPSIS思想的改进灰色关联法及其在方案评估中的应用

提出了一种基于TOPSIS思想的改进灰色关联法,方法采用了TOPSIS思想,通过标准化处理,能够将灰色关联法给出的评估结果转换为,TOPSIS方法所要用到的与最优/最劣解的距离,从而给出一个稳定的评估结果,弥补了传统灰色关联法受全局极值影响大的缺点.经实例分析证明,方法可以应用于方案评估中,并能够得出可行、稳定、科学的评估结果.     

TOPSIS for bi-level MODM problems

TOPSIS (technique for order preference by similarity to ideal solution) is a multiple criteria method to identify solutions from a finite set of alternatives based upon simultaneous minimization of distance from an ideal point and maximization of distance from a nadir point. This paper proposes a fuzzy TOPSIS algorithm to solve bi-level multi-objective decision-making (BL-MODM) problems, and in which the objective function at each level are non-linear functions which are to be maximized. The proposed model for getting the satisfactory solution of the BL-MODM problems includes the membership functions for the upper level decision variables vector with possible tolerances, the membership function of the distance function from the positive ideal solution (PIS) and the membership function of the distance function from the negative ideal solution (NIS). A numerical illustrative example is given to clarify the proposed TOPSIS approach of this paper.