Hesitant interval-valued Pythagorean fuzzy VIKOR method

2018 ◽  
Vol 34 (5) ◽  
pp. 754-789 ◽  
Author(s):  
Wei Yang ◽  
Yongfeng Pang
Keyword(s):  
Vikor Method ◽  
Fuzzy Vikor ◽  
Interval Valued

Accurate location planning for a wind-powered hydrogen refueling station: Fuzzy VIKOR method

2021 ◽  
Vol 46 (67) ◽  
pp. 33360-33374
Author(s):  
Mostafa Rezaei ◽  
Sulaiman Ali Alharbi ◽  
Armin Razmjoo ◽  
Mohamed A. Mohamed
Keyword(s):  
Vikor Method ◽  
Location Planning ◽  
Fuzzy Vikor

A Fuzzy VIKOR method to analyze the risks in lean manufacturing implementation

2020 ◽  
Author(s):  
R.K.A. Bhalaji ◽  
S. Bathrinath ◽  
S. Saravanasankar
Keyword(s):  
Lean Manufacturing ◽  
Vikor Method ◽  
Fuzzy Vikor

scholarly journals Group decision-making approach for flood vulnerability identification using the fuzzy VIKOR method

2015 ◽  
Vol 15 (4) ◽  
pp. 863-874 ◽  
Author(s):  
G. Lee ◽  
K. S. Jun ◽  
E.-S. Chung
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Consensus Building ◽  
Vikor Method ◽  
Flood Vulnerability ◽  
Fuzzy Vikor ◽  
Risk Vulnerability

Abstract. This study proposes an improved group decision making (GDM) framework that combines the VIKOR method with data fuzzification to quantify the spatial flood vulnerability including multiple criteria. In general, GDM method is an effective tool for formulating a compromise solution that involves various decision makers since various stakeholders may have different perspectives on their flood risk/vulnerability management responses. The GDM approach is designed to achieve consensus building that reflects the viewpoints of each participant. The fuzzy VIKOR method was developed to solve multi-criteria decision making (MCDM) problems with conflicting and noncommensurable criteria. This comprising method can be used to obtain a nearly ideal solution according to all established criteria. This approach effectively can propose some compromising decisions by combining the GDM method and fuzzy VIKOR method. The spatial flood vulnerability of the southern Han River using the GDM approach combined with the fuzzy VIKOR method was compared with the spatial flood vulnerability using general MCDM methods, such as the fuzzy TOPSIS and classical GDM methods (i.e., Borda, Condorcet, and Copeland). As a result, the proposed fuzzy GDM approach can reduce the uncertainty in the data confidence and weight derivation techniques. Thus, the combination of the GDM approach with the fuzzy VIKOR method can provide robust prioritization because it actively reflects the opinions of various groups and considers uncertainty in the input data.

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