A Novel Trapezoidal Bipolar Fuzzy TOPSIS Method for Group Decision-Making

Akram, Muhammad; Arshad, Muhammad

doi:10.1007/s10726-018-9606-6

Cited by 76 publications

(53 citation statements)

References 25 publications

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“…Alghamdi et al [29] introduced the MCDM methods TOPSIS and ELECTRE I, in bipolar fuzzy environment. Akram and Arshad [30] presented a novel trapezoidal bipolar fuzzy TOPSIS method for group decision-making. Akram et al [31] used bipolar fuzzy TOPSIS and bipolar fuzzy ELECTRE I methods in medical diagnosis.…”

Section: Introductionmentioning

confidence: 99%

Multiple-Attribute Decision Making ELECTRE II Method under Bipolar Fuzzy Model

2019

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The core aim of this paper is to provide a new multiple-criteria decision making (MCDM) model, namely bipolar fuzzy ELimination and Choice Translating REality (ELECTRE) II method, by combining the bipolar fuzzy set with ELECTRE II technique. It can be used to solve the problems having bipolar uncertainty. The proposed method is established by defining the concept of bipolar fuzzy strong, median and weak concordance as well as discordance sets and indifferent set to define two types of outranking relations, namely strong outranking relation and weak outranking relation. The normalized weights of criteria, which may be partly or completely unknown for decision makers, are calculated by using an optimization technique, which is based on maximizing deviation method. A systematic iterative procedure is applied to strongly outrank as well as weakly outrank graphs to determine the ranking of favorable actions or alternatives or to choose the best possible solution. The implementation of the proposed method is presented by numerical examples such as selection of business location and to chose the best supplier. A comparative analysis of proposed ELECTRE II method is also presented with already existing multiple-attribute decision making methods, including Technique for the Order of Preference by Similarity to an Ideal Solution (TOPSIS) and ELECTRE I under bipolar fuzzy environment by solving the problem of business location.

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Section: Introductionmentioning

confidence: 99%

Multiple-Attribute Decision Making ELECTRE II Method under Bipolar Fuzzy Model

2019

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“…YinYang bipolar fuzzy set theory (or bipolar fuzzy set theory) was initiated by Zhang [29,30] as a generalization of fuzzy set theory [31] to deal with the bipolar judgmental thinking of human reasoning. Akram and Arshad [32] introduced bipolar fuzzy linguistic variables and bipolar fuzzy numbers as an extended version of bipolar fuzzy sets. Alghamdiet al [33] proposed multi-criteria decision-making methods using bipolar fuzzy information.…”

Section: Introductionmentioning

confidence: 99%

Multi-Criteria Group Decision-Making for Selection of Green Suppliers under Bipolar Fuzzy PROMETHEE Process

2020

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The preference ranking organization method for enrichment of evaluations (PROMETHEE) method considers a significant outranking class of multi-criteria decision analysis (MCDA), as it is easy to deal with its simple computations. In the PROMETHEE, different preference functions are used according to the type and nature of attributes or criteria that demonstrate the clearness and reliability of this method. This study provides a new version of the PROMETHEE method using bipolar fuzzy information, named the bipolar fuzzy PROMETHEE method. Bipolar fuzzy sets or numbers constitute an asymmetrical relationship between two judgmental factors of human reasoning. Vague and imprecise knowledge is characterized by bipolar fuzzy linguistic terms which are further represented in the form of trapezoidal bipolar fuzzy numbers. The trapezoidal bipolar fuzzy numbers are used by analysts to assign the preferences of alternatives on the basis of criteria. Further, a ranking function of bipolar fuzzy numbers is considered to access the crisp real preferences of alternatives. The entropy weighting information is employed to calculate the weights of attributes by considering the condition of normality. A numerical example such as the selection of green suppliers by using the bipolar fuzzy PROMETHEE is performed on the basis of the usual criterion preference function in order to explain the procedure of the proposed method. Comparable results are derived by using the combination of linear and level preference functions. The results obtained by using different types of preference functions are the same, representing the authenticity of the proposed bipolar fuzzy PROMETHEE method.

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“…Recently, Shumaiza et al [7] have proposed group decision-making based on the VIKOR method with trapezoidal bipolar fuzzy information. Akram and Arshad [8] proposed a novel trapezoidal bipolar fuzzy TOPSIS method for group decision-making. Alcantud et al [9] proposed a novel modelization of the party formation process, in which citizens' private opinions are described by means of continuous fuzzy profiles.…”

Section: Introductionmentioning

confidence: 99%

A Study on Hypergraph Representations of Complex Fuzzy Information

et al. 2019

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The paradigm shift prompted by Zadeh’s fuzzy sets in 1965 did not end with the fuzzy model and logic. Extensions in various lines have produced e.g., intuitionistic fuzzy sets in 1983, complex fuzzy sets in 2002, or hesitant fuzzy sets in 2010. The researcher can avail himself of graphs of various types in order to represent concepts like networks with imprecise information, whether it is fuzzy, intuitionistic, or has more general characteristics. When the relationships in the network are symmetrical, and each member can be linked with groups of members, the natural concept for a representation is a hypergraph. In this paper we develop novel generalized hypergraphs in a wide fuzzy context, namely, complex intuitionistic fuzzy hypergraphs, complex Pythagorean fuzzy hypergraphs, and complex q-rung orthopair fuzzy hypergraphs. Further, we consider the transversals and minimal transversals of complex q-rung orthopair fuzzy hypergraphs. We present some algorithms to construct the minimal transversals and certain related concepts. As an application, we describe a collaboration network model through a complex q-rung orthopair fuzzy hypergraph. We use it to find the author having the most outstanding collaboration skills using score and choice values.

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A Novel Trapezoidal Bipolar Fuzzy TOPSIS Method for Group Decision-Making

Cited by 76 publications

References 25 publications

Multiple-Attribute Decision Making ELECTRE II Method under Bipolar Fuzzy Model

Multiple-Attribute Decision Making ELECTRE II Method under Bipolar Fuzzy Model

Multi-Criteria Group Decision-Making for Selection of Green Suppliers under Bipolar Fuzzy PROMETHEE Process

A Study on Hypergraph Representations of Complex Fuzzy Information

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