Decision-making methods based on hybrid mF models

Akram, Muhammad; Ali, Ghous; Waseem, Neha; Davvaz, Bijan

doi:10.3233/jifs-172282

Cited by 26 publications

(10 citation statements)

References 21 publications

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“…We propose the method of mF linguistic TOPSIS for MCGDM , in which L v is the linguistic variable, i.e., appearance and M = {A m 1 , A m 2 , A m 3 , A m 4 , A m 5 } is the set of appearance of five different models, whereas V = {Less attractive, Fairly cute, Quite pretty, Very beautiful} is the set of linguistic values of appearance. Decision-makers have to evaluate the models on the basis of the linguistic values of their appearance and they have to design a physical domain in which appearance takes its quantitative values, i.e., P d = [10,100]. The physical domain for linguistic values of appearance is given as follows: The physical domain of each linguistic value shows the range of marks given by a group of decision-makers out of 100.…”

Section: Models Ranking According To Their Appearancementioning

confidence: 99%

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Group Decision-Making Based on m-Polar Fuzzy Linguistic TOPSIS Method

2019

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The fuzzy linguistic approach provides favorable outputs in several areas, whose description is relatively qualitative. The encouragement for the utilization of sentences or words instead of numbers is that linguistic characterizations or classifications are usually less absolute than algebraic or arithmetical ones. In this research article, we animate the m-polar fuzzy (mF) linguistic approach and elaborate it with real life examples and tabular representation to develop the affluence of linguistic variables based on mF approach. As an extension of the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, we develop an m-polar fuzzy linguistic TOPSIS approach for multi-criteria group decision-making (MCGDM). It is used to evaluate the best alternative, to get more authentic and comparable results and to handle the real life problems of having multi-polar information in terms of linguistic variables and values. In this approach decision-makers contribute their estimations in the form of linguistic term sets. To show the efficiency and compatibility of the proposed approach, we compare it with the m-polar fuzzy linguistic ELECTRE-I (Elimination and Choice Translating Reality) approach. Finally, we draw a flow chart of our proposed approach as an algorithm and generate a computer programming code.

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Section: Models Ranking According To Their Appearancementioning

confidence: 99%

“…Akram and Adeel [9] introduced novel hybrid decision-making methods based on mF rough information. Further, Akram et al [10] worked on decision-making methods based on hybrid mF models. Furthermore, Akram [11] introduced many new concepts including mF graphs, mF line graphs, mF labeling graphs and certain metrics in mF graphs.…”

Section: Introductionmentioning

confidence: 99%

Group Decision-Making Based on m-Polar Fuzzy Linguistic TOPSIS Method

2019

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“…The concept of HFS and IHFS are extensively used in many problems such as Mahmood et al [18] worked on the generalised aggregation operators for Cubic HFSs, Ullah et al [19] introduced bipolar-valued HFSs, Farhadinia [20] developed the concept of information measures for HFSs and interval-valued HFSs and Zhai et al [21] utilised measures of probabilistic interval-valued IHFSs and the application in reducing excessive medical examinations. Some other work in these fields, we may refer to [22][23][24][25][26]. Recently, Wang et al [27] developed the concept of PHFS and its application in multi-attribute decision making are examined.…”

Section: Introductionmentioning

confidence: 99%

TOPSIS Method and Similarity Measures Based on Cosine Function Using Picture Hesitant Fuzzy Sets and its Applications to Strategic Decision Making

Mahmood

Ahmad

Ali

et al. 2020

Fuzzy Information and Engineering

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Picture hesitant fuzzy set (PHFS) is a recently developed tool to cope with uncertain and awkward information in realistic decision issues and is applicable where opinions are of more than two types, i.e., yes, no, abstinence and refusal. Similarity measures (SMs) in a data mining context are distance with dimensions representing features of the objects. Keeping the advantages of the above analysis, in this manuscript, the authors proposed SMs for PHFSs, including cosine SMs for PHFSs, SMs for PHFSs based on cosine function, and SMs for PHFSs based on cotangent function. Further, entropy measure, TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) based on correlation coefficient are investigated for PHFSs. Further, some weighted SMs are also proposed and then applied to the strategic decision-making problem and the results are discussed. Moreover, we take two illustrative examples to compare the established work with existing drawbacks and also show that the existing drawback cannot solve the problem of established work. But on the other hand, the new approach can easily solve the problem of the existing drawback. Finally, the advantages of the new approach are discussed.

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“…Generalized approximations in (∈, ∈ ∨q)-fuzzy ideals in quantales was proposed by Shabir (2018c, 2019). Some decision-making methods related to hesitant fuzzy sets and graph theory, also hybrid mF models, can be seen in (Akram et al 2018;Naz and Akram 2019). Molodtsov (1999) presented the soft set theory to overcome the difficulties mostly related to economics, medicine, environment, engineering and social sciences.…”

Section: Introductionmentioning

confidence: 99%

Generalized approximation of substructures in quantales by soft relations

2019

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The present work is conducted to investigate the relationship among rough sets, soft sets and quantales. The concept of generalized approximation of substructures in quantales by soft relations is introduced, which is an extended notion of a rough quantale and a soft quantale. This paper is focused on studying the rough sets within the context of algebraic structure quantale using soft reflexive and soft compatible relations. Further, we put forward the concepts of aftersets and foresets, which provide a new research idea for soft rough algebraic research. Some basic concepts, operations and related properties with regard to soft binary relations are proposed. Keywords Quantales • Ideals of quantales • Approximation by soft relations • Approximation of ideals in quantales • Quantale homomorphism Mathematics Subject Classification 08Axx • 08A72 Communicated by Anibal Tavares de Azevedo.

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Decision-making methods based on hybrid mF models

Cited by 26 publications

References 21 publications

Group Decision-Making Based on m-Polar Fuzzy Linguistic TOPSIS Method

Group Decision-Making Based on m-Polar Fuzzy Linguistic TOPSIS Method

TOPSIS Method and Similarity Measures Based on Cosine Function Using Picture Hesitant Fuzzy Sets and its Applications to Strategic Decision Making

Generalized approximation of substructures in quantales by soft relations

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