Intuitionistic fuzzy multi-attribute group decision-making with an application to plant location selection based on a new extended VIKOR method

Gupta, Pankaj; Mehlawat, Mukesh Kumar; Grover, Nishtha

doi:10.1016/j.ins.2016.07.058

Cited by 111 publications

(37 citation statements)

References 33 publications

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“…has been researched little, especially in the Pythagorean fuzzy environment. VIKOR method is an effective method to achieve compromise solution and it can trade off the majority's maximum group utility and the opponent's minimum individual regret . Opricovic and Tzeng compared the extended VIKOR method with three other multiple criteria decision‐making methods: TOPSIS, PROMETHEE, and ELECTRE.…”

Section: Introductionmentioning

confidence: 99%

“…Zhang and Xing extended the VIKOR approach to multiple attribute decision‐making problems with probabilistic linguistic information. The VIKOR method has been extended to accommodate interval values, intuitionistic fuzzy value, interval type‐2 fuzzy values, probability linguistic fuzzy values, triangular intuitionistic fuzzy values, hesitant fuzzy values, linguistic hesitant intuitionistic fuzzy values, and so on. The VIKOR method has been applied extensively, including the site selection, material selection, supplier selection, hospital service evaluation, robot selection, airline service evaluation, and so on.…”

Section: Introductionmentioning

confidence: 99%

“…VIKOR method is an effective method to achieve compromise solution and it can trade off the majority's maximum group utility and the opponent's minimum individual regret. [39][40][41][42] Opricovic and Tzeng 43 compared the extended VIKOR method with three other multiple criteria decision-making methods: TOPSIS, PROMETHEE, and ELECTRE. Zhang and Xing 44 extended the VIKOR approach to multiple attribute decision-making problems with probabilistic linguistic information.…”

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confidence: 99%

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Hesitant interval-valued Pythagorean fuzzy VIKOR method

Yang

Pang

2018

Int J Intell Syst

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In this article, we investigate multiple attribute decision‐making problems with hesitant interval‐valued Pythagorean fuzzy information. First, the concepts of hesitant interval‐valued Pythagorean fuzzy set are defined, and the operation laws, the score function, and accuracy function have been developed. Then several distance measures for hesitant interval‐valued Pythagorean fuzzy values have been presented including the Hamming distance, Euclidean distance, and generalized distance, and so on. Based on the operational laws, a series of aggregation operators have been developed including the hesitant interval‐valued Pythagorean fuzzy weighted averaging (HIVPFWA) operator, the hesitant interval‐valued Pythagorean fuzzy geometric weighted averaging (HIVPFGWA) operator, the hesitant interval‐valued Pythagorean fuzzy ordered weighed averaging (HIVPFOWA) operator, and hesitant interval‐valued Pythagorean fuzzy ordered weighed geometric averaging (HIVPFOWGA) operator. By using the generalized mean operator, we also develop the generalized hesitant interval‐valued Pythagorean fuzzy weighed averaging (GHIVPFWA) operator, the generalized hesitant interval‐valued Pythagorean fuzzy weighed geometric averaging (GHIVPFWGA) operator, the generalized hesitant interval‐valued Pythagorean fuzzy ordered weighted averaging (GHIVPFOWA) operator, and generalized hesitant interval‐valued Pythagorean fuzzy ordered weighted geometric averaging (GHIVPFOWGA) operator operator. We further develop several hybrid aggregation operators including the hesitant interval‐valued Pythagorean fuzzy hybrid averaging (HIVPFHA) operator and the generalized hesitant interval‐valued Pythagorean fuzzy hybrid averaging (GHIVPFHA) operator. Based on the distance measures and the aggregation operators, we propose a hesitant interval‐valued Pythagorean fuzzy VIKOR method to solve multiple attribute decision problems with multiple periods. Finally, an illustrative example for evaluating the metro project risk is given to demonstrate the feasibility and effectiveness of the proposed method.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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Hesitant interval-valued Pythagorean fuzzy VIKOR method

Yang

Pang

2018

Int J Intell Syst

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“…On the other hand, due to the complexity of decision-making issues and the conflict between the indicators of the EGS power generation project, the evaluation results may not be accepted by all policy makers. Based on the above problems, this paper proposes a preferred framework for the EGS power generation investment plan based on fuzzy set theory [7][8] and multi-criteria compromised sorting method [9][10][11].The use of triangular fuzzy numbers to represent the decision values of each candidate item prevents the loss of decision information. Through the multi-criteria compromised sorting method, ranking of a series of solutions with multiple conflicts or inconsistent indicators can be achieved, so as to better complete the optimization of the investment scheme of the EGS power generation.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Enhanced Geothermal System Power Generation Investment Scheme Based on Fuzzy VIKOR Model

Guo

Cheng

2018

E3S Web Conf.

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In the future, Enhanced Geothermal System (EGS) power generation will be a hot spot for new energy investment development. How to optimize the EGS power generation investment program is an important issue to be solved by the government and enterprises. In order to improve the accuracy of the EGS investment project evaluation, this paper proposes a technical route to optimize the EGS power generation investment program. It comprehensively considers the ambiguity of the decision attributes and the conflict between the indicators. The index is calculated using the entropy method and the order relationship method. Comprehensive weights; using triangular fuzzy numbers instead of exact numbers to reduce the loss of decision information; using a multi-criteria compromised sorting method to obtain trade-off solutions to solve the problem that investment plans cannot be accepted by all decision makers when there are multiple conflicting indicators. Finally, taking an enterprise's EGS power generation project as an example, the effectiveness and rationality of the optimized technology route for the EGS power generation investment program are verified.

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“…However, with the increasing complexity of real decision problems, decision makers frequently face the challenge of characterizing their preferences in an uncertain context. This opens an important application field of fuzzy set theory and granular computing techniques: fuzzy decision making [2,8,10,14,23,33,39,41,47]. As stated by Pedrycz and Chen [25], fuzzy decision making including its underlying methodology, the plethora of algorithmic developments, and a rich and diversified slew of application studies form a cornerstone of fuzzy sets.…”

Section: Introductionmentioning

confidence: 99%

Analysis of fuzzy Hamacher aggregation functions for uncertain multiple attribute decision making

Tang

et al. 2017

Information Sciences

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As generalizations of algebraic and Einstein t-norms and t-conorms, Hamacher t-norm and t-conorm have been widely applied in fuzzy multiple attribute decision making (MADM) to combine assessments on each attribute, which are generally expressed by Atanassov"s intuitionistic fuzzy (AIF) numbers, interval-valued intuitionistic fuzzy (IVIF) numbers, hesitant fuzzy (HF) elements, and dual hesitant fuzzy (DHF) elements. Due to the fact that AIF numbers and HF elements are special cases of IVIF numbers and DHF elements, respectively, two propositions can be established from analyzing numerical examples and real cases concerning MADM with IVIF and DHF assessments in the literature: (1) the monotonicity of alternative scores derived from Hamacher arithmetic and geometric aggregation operators with respect to the parameter r in Hamacher t-norm and t-conorm; and (2) the relationship between alternative scores generated by Hamacher arithmetic and geometric aggregation operators, given the same r. Here, we provide the theoretical proof of these two propositions in the context of MADM with IVIF and DHF assessments.With the theoretical support of these propositions, the meaning of r in MADM is explained, and a new method is proposed to compare alternatives in MADM with consideration of all possible values of r. Two numerical examples are solved by the proposed method and the other two existing methods to demonstrate the applicability and validity of the proposed method and highlight its advantages.

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Intuitionistic fuzzy multi-attribute group decision-making with an application to plant location selection based on a new extended VIKOR method

Cited by 111 publications

References 33 publications

Hesitant interval-valued Pythagorean fuzzy VIKOR method

Hesitant interval-valued Pythagorean fuzzy VIKOR method

Optimization of Enhanced Geothermal System Power Generation Investment Scheme Based on Fuzzy VIKOR Model

Analysis of fuzzy Hamacher aggregation functions for uncertain multiple attribute decision making

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