Multi Criteria Decision Making menggunakan Operator Group Generalized Interval Value Pythagorean Fuzzy

Multi Criteria Decision Making (MCDM) adalah proses penentuan solusi terbaik dalam suatu masalah berdasarkan kriteria yang telah ditentukan. Dalam berbagai kasus, pengambil keputusan sulit untuk menyatakan pendapatnya dalam angka yang tegas. Oleh karena itu, penggunaan bilangan fuzzy dianggap lebih efisien. Salah satu bilangan fuzzy yang digunakan dalam kasus MCDM adalah Interval Value Pythagorean Fuzzy Number (IVPFN). Informasi fuzzy pada kasus MCDM dinyatakan dalam IVPFN. Akurasi informasi fuzzy dinilai oleh Group Generalized Parameter (GGP) yang dinyatakan dengan cara yang sama seperti informasi fuzzy, yaitu dengan IVPFN. Informasi fuzzy dan GGP selanjutnya diagregasi menggunakan operator Group Generalized Interval Value Pythagorean Fuzzy Weighted Average (GGIVPFWA) dan Group Generalized Interval Value Pythagorean Fuzzy Weighted Geometric (GGIVPFWG). Kedua operator tersebut bertujuan untuk menemukan alternatif terbaik yang dapat dipilih. Hasil keputusan dari operator GGIVPFWA dan GGIVPFWG selanjutnya diverifikasi menggunakan weighted similarity measure dan menunjukkan bahwa kedua operator tersebut dapat menyelesaikan masalah MCDM secara efektif dan akura

A new outranking method for multicriteria decision making with complex Pythagorean fuzzy information

[EN]This article contributes to the advancement and evolution of outranking decision-making methodologies, with a novel essay on the ELimination and Choice Translating REality (ELECTRE) family of methods. Its primary target is to unfold the constituents and expound the implementation of the ELECTRE II method for group decision making in complex Pythagorean fuzzy framework. This results in the complex Pythagorean fuzzy ELECTRE II method. By inception, it is intrinsically superior to models using one-dimensional data. It is designed to perform the pairwise comparisons of the alternatives using the core notions of concordance, discordance and indifferent sets, which is then followed by the construction of complex Pythagorean fuzzy concordance and discordance matrices. Further, the strong and weak outranking relations are developed by the comparison of concordance and discordance indices with the concordance and discordance levels. Later, the forward, reverse and average rankings of the alternatives are computed by the dint of strong and weak outranking graphs. This methodology is supported by a case study for the selection of wastewater treatment process, and by a numerical example for the selection of the best cloud solution for a big data project. Its consistency is confirmed by an effectiveness test and comparison analysis with the Pythagorean fuzzy ELECTRE II and complex Pythagorean fuzzy ELECTRE I methodsPublicación en abierto financiada por el Consorcio de Bibliotecas Universitarias de Castilla y León (BUCLE), con cargo al Programa Operativo 2014ES16RFOP009 FEDER 2014-2020 DE CASTILLA Y LEÓN, Actuación:20007-CL - Apoyo Consorcio BUCL

The generalized dice similarity measures for multiple attribute decision making with hesitant fuzzy linguistic information

In this paper, we shall present some novel Dice similarity measures of hesitant fuzzy linguistic term sets and the generalized Dice similarity measures of hesitant fuzzy linguistic term sets and indicate that the Dice similarity measures and asymmetric measures (projection measures) are the special cases of the generalized Dice similarity measures in some parameter values. Then, we propose the generalized Dice similarity measures-based multiple attribute decision making models with hesitant fuzzy linguistic term sets. Finally, a practical example concerning the evaluation of the quality of movies is given to illustrate the applicability and advantage of the proposed generalized Dice similarity measure

Some q-rung orthopair fuzzy Muirhead means with their application to multi-attribute group decision making

Recently proposed q-rung orthopair fuzzy set (q-ROFS) is a powerful and effective tool to describe fuzziness, uncertainty and vagueness. The prominent feature of q-ROFS is that the sum and square sum of membership and non-membership degrees are allowed to be greater than one with the sum of qth power of the membership degree and qth power of the non-membership degree is less than or equal to one. This characteristic makes q-ROFS more powerful and useful than intuitionistic fuzzy set (IFS) and Pythagorean fuzzy set (PFS). The aim of this paper is to develop some aggregation operators for fusing q-rung orthopair fuzzy information. As the Muirhead mean (MM) is considered as a useful aggregation technology which can capture interrelationships among all aggregated arguments, we extend the MM to q-rung orthopair fuzzy environment and propose a family of q-rung orthopair fuzzy Muirhead mean operators. Moreover, we investigate some desirable properties and special cases of the proposed operators. Further, we apply the proposed operators to solve multi-attribute group decision making (MAGDM) problems. Finally, a numerical instance as well as some comparative analysis are provided to demonstrate the validity and superiorities of the proposed method