A GRP-basedHesitant Fuzzy Multiple Attribute Decision MakingMethod and Its Application to E-Commerce Risk Assessment

With respect to multiple attribute decision making (MADM) problems in which the attribute values take the form of hesitant fuzzy elements, the traditional grey relational projection (GRP) method is extended to solve multiple attribute decision making problems under hesitant fuzzy environment. Based on the hesitant fuzzy decision matrix provided by decision makers, all feasible alternatives are ranked according to the descending order of relative grey relational projections, and the most desirable alternative(s) should have the largest grey relational projection on positive ideal solution and the smallest grey relational projection on negative ideal solution. Finally, a numerical example of e-commerce risk assessment is given to illustrate the application of the proposed method

Hesitant fuzzy network topsis methods with the incorporation of z-numbers and social network analysis for small and large scale group decision making

It is critical to arrive at an acceptable level of consensus in a group for an agreeable and implementable decision. The evaluation of alternatives in conventional TOPSIS decision making does not take into account the inherent vagueness of information as it requires a systematic decision-making process in which relies on numerous conditions and unpredictable situations. It is common in deciding the best choice with the highest satisfaction degree that are evaluated based on attributes. However, two or more alternatives with the same or nearest satisfaction degree would lead to hesitancy in the decision. Thus, fuzzy network TOPSIS is incorporated with the hesitant fuzzy set is developed namely hesitant fuzzy network TOPSIS. Nevertheless, the reliability of decisions by experts and the complexity in large scale are less highlighted in hesitant fuzzy network TOPSIS. Therefore, this study aims in formulating hesitant fuzzy network TOPSIS with the incorporation of Z-numbers. The formulation also implies social network analysis for large-scale group decision making. In this study, four new fuzzy network TOPSIS are developed in small scale and large-scale group decision making. The proposed methods enhance the transparency and reliability by incorporating fuzzy network and Z numbers respectively. In addition, social network analysis is suitable for dealing with the complexity involved in large scale group decision making. For the practicality and the effectiveness of the proposed methods in a realistic scenario, a case study of stock selection and the analysis of results comparing proposed methods to the established methods has been considered. The ranking of the proposed methods are validated comparatively using performance indicators namely Spearman rho correlation, Root Means Squared Error, and Absolute Distance by assuming ranking based on Return on Investment as a benchmarking. Based on the case study, the proposed methods outperform the established methods in terms of average rank position. In conclusion, the proposed methods contribute significantly toward the implementation of small scale and large scale group decision making using hesitant fuzzy set, fuzzy network and Z numbers

HFMADM method based on nondimensionalization and its application in the evaluation of inclusive growth

Inclusive growth, which encompasses different aspects of life, is a growth pattern that allows all people to participate in and contribute to growth process. In this paper, a novel hesitant fuzzy multiple attribute decision making (HFMADM) approach based on the nondimensionalization of decision making attributes is presented and then applied to the evaluation of inclusive growth in China. Firstly, a novel generalized hesitant fuzzy distance measure is proposed to calculate the difference and deviation between two hesitant fuzzy elements (hfes) without adding any values into the shorter hesitant fuzzy element. Secondly, the coefficient of variation and efficacy coefficient method are extended to accommodate hesitant fuzzy environment and then used to cope with HFMADM. In the analysis process, non-dimensional treatment for hesitant fuzzy decision data is produced. Lastly, the method proposed in this paper is applied to an example of inclusive growth evaluation problem under hesitant fuzzy environment and the case study illustrates the practicality of the proposed method. Beyond that, a comparative analysis with some other approaches is also conducted to demonstrate the superiority and feasibility of the proposed method

A hybrid intuitionistic fuzzy multi-criteria group decision making approach for supplier selection

Due to the increasing competition of globalization, selection of the most appropriate supplier is one of the key factors for asupply chain management’s success. Due to conflicting evaluations and insufficient information about the criteria, Intuitionisticfuzzy sets (IFSs) considered as animpressive tool and utilized to specify the relative importance of the criteria. The aim of this paper is to develop a new approach for solving the decision making processes. Thusan intuitionistic fuzzy multi-criteria group decision making approach is proposed. Interval-valued intuitionistic fuzzy ordered weighted aggregation (IIFOWA) is utilized to aggregate individual opinions of decision makers into a group opinion. A linear programming model is used to obtain the weights of the criteria.Then acombined approach based onGRAand TOPSIS method is introduced and applied to the ranking and selection of the alternatives. Finally a numerical example for supplier selection is given to illustrate the feasibility and effectiveness of the proposed method. A combined method based on GRA and TOPSIS associated with intuitionistic fuzzy set has enormous chance of success for multi-criteria decision-making problems due to containing vague perception of decision makers’ opinions. Therefore, in future, intuitionistic fuzzy set can be used for dealing with uncertainty in multi-criteria decision-making problems such as project selection, manufacturing systems, pattern recognition, medical diagnosis and many other areas of management decision problems

Multicriteria Group Decision Making by Using Trapezoidal Valued Hesitant Fuzzy Sets

The concept of trapezoidal valued hesitant fuzzy set is introduced. Notion for distance between any two trapezoidal valued hesitant fuzzy elements is given. Using this proposed distance measure, we extend the technique for order preference by similarity to ideal solution for trapezoidal valued hesitant fuzzy sets. An example is constructed to show usefulness of this extension for multicriteria group decision making, where the opinions about the criteria values are expressed as trapezoidal valued hesitant fuzzy set

A New Method of Multiattribute Decision-Making Based on Interval-Valued Hesitant Fuzzy Soft Sets and Its Application

Combining interval-valued hesitant fuzzy soft sets (IVHFSSs) and a new comparative law, we propose a new method, which can effectively solve multiattribute decision-making (MADM) problems. Firstly, a characteristic function of two interval values and a new comparative law of interval-valued hesitant fuzzy elements (IVHFEs) based on the possibility degree are proposed. Then, we define two important definitions of IVHFSSs including the interval-valued hesitant fuzzy soft quasi subset and soft quasi equal based on the new comparative law. Finally, an algorithm is presented to solve MADM problems. We also use the method proposed in this paper to evaluate the importance of major components of the well drilling mud pump

Hesitant fuzzy multi-criteria decision making methods based on Heronian mean

Among several extensions of fuzzy set theory, the concept introduced by Torra and Narukawa (2009) in defining hesitant fuzzy set is interesting and practical. In this paper we introduce and study new methods for dealing with MCDM (multi-criteria decision making) problems under the hesitant fuzzy environment. First, we propose and discuss the notion of hesitant fuzzy Heronian mean operators. By using these operators, we can portray the relationship of the criteria effectively. Then, the numerical examples are provided and comparative analyses with other aggregation operators are not neglected. Furthermore, the weighted forms of the hesitant fuzzy Heronian mean operators are defined for MCDM problem, based on which, new MCDM methods are proposed. The MCDM methods presented in this paper can provide an effective manner to assist the decision maker in making his/her decision. An example about dormitory construction projection selection is given to show the effectiveness of the proposed method. First published online: 04 Nov 201

A method based on TOPSIS and distance measures for hesitant fuzzy multiple attribute decision making

The aim of this paper is to provide a methodology to hesitant fuzzy multiple attribute decision making using technique for order preference by similarity to ideal solution (TOPSIS) and distance measures. Firstly, the inadequacies of the existing hesitant fuzzy TOPSIS method are analyzed in detail. Then, based on the developed hesitant fuzzy ordered weighted averaging weighted aver-aging distance (HFOWAWAD) measure, a modified hesitant fuzzy TOPSIS, called HFOWAWAD-TOPSIS is introduced for hesitant fuzzy multiple attribute decision making problems. Moreover, the advantages and some special cases of the HFOWAWAD-TOPSIS are presented. Finally, a numerical example about energy policy selection is provided to illustrate the practicality and feasibility of the developed approach