scholarly journals q-Rung Orthopair Fuzzy TOPSIS Method for Green Supplier Selection Problem

2021 ◽  
Vol 13 (2) ◽  
pp. 985
Author(s):  
Adem Pınar ◽  
Rouyendegh Babak Daneshvar ◽  
Yavuz Selim Özdemir
Keyword(s):  
Supplier Selection ◽  
Fuzzy Topsis ◽  
Problem Structure ◽  
Topsis Method ◽  
Green Supplier Selection ◽  
Selection Problems ◽  
Environmental Criteria ◽  
Selection Approach ◽  
Intuitionistic Fuzzy Topsis ◽  
Supplier Selection Problem

Supply chain management is to improve competitive stress. In today’s world, competitive terms and customer sense have altered in favor of an environmentalist manner. As a result of this, green supplier selection has become a very important topic. In the green supplier selection approach, agility, lean process, sustainability, environmental sensitivity, and durability are pointed. Like the classical supplier selection problems, environmental criteria generally emphasize green supplier selection. However, these two problem approaches are different from each other in terms of carbon footprint, water consumption, environmental and recycling applications. Due to the problem structure, a resolution is defined that includes an algorithm based on q-Rung Orthopair Fuzzy (q-ROF) TOPSIS method. Brief information about q-ROF sets is given before the methodology of the q-ROF model is introduced. By using the proposed method and q-ROF sets, an application was made with today’s uncertain conditions. In the conclusion part, a comparison is made with classical TOPSIS, Intuitionistic Fuzzy TOPSIS and q-ROF TOPSIS methodology. As a result, more stable and accurate results are obtained with q-ROF TOPSIS.

scholarly journals Circular intuitionistic fuzzy TOPSIS method with vague membership functions: Supplier selection application context

2021 ◽  
Vol 27 (1) ◽  
pp. 24-52
Author(s):  
Cengiz Kahraman ◽  
◽  
Nurşah Alkan ◽  
Keyword(s):  
Fuzzy Sets ◽  
Membership Function ◽  
Supplier Selection ◽  
Three Dimensional ◽  
Fuzzy Topsis ◽  
Intuitionistic Fuzzy Sets ◽  
Topsis Method ◽  
Intuitionistic Fuzzy ◽  
Intuitionistic Fuzzy Topsis ◽  
The Membership Function

The membership function of a general type-2 fuzzy set is three-dimensional in order to incorporate its vagueness through the third dimension. Similarly, Circular intuitionistic fuzzy sets (CIFSs) have been recently introduced by Atanassov (2020) as a new extension of intuitionistic fuzzy sets, which are represented by a circle representing the vagueness of the membership function. CIFSs allow decision-makers to express their judgments including this vagueness. In this study, the TOPSIS method, which is one of the most used multi-criteria decision-making methods is extended to its CIF version. The proposed CIF-TOPSIS methodology is applied to the supplier selection problem. Then, a sensitivity analysis based on criteria weights is conducted to check the robustness of the proposed approach. A comparative analysis with single-valued intuitionistic fuzzy TOPSIS method is also performed to verify the developed approach and to demonstrate its effectiveness

Sustainable supplier selection: A multi-criteria intuitionistic fuzzy TOPSIS method

2019 ◽  
Vol 50 ◽  
pp. 9-24 ◽  
Author(s):  
Ashkan Memari ◽  
Ahmad Dargi ◽  
Mohammad Reza Akbari Jokar ◽  
Robiah Ahmad ◽  
Abd. Rahman Abdul Rahim
Keyword(s):  
Supplier Selection ◽  
Fuzzy Topsis ◽  
Topsis Method ◽  
Intuitionistic Fuzzy ◽  
Sustainable Supplier Selection ◽  
Intuitionistic Fuzzy Topsis

scholarly journals Application of Fuzzy-TOPSIS Method in Supporting Supplier Selection with Focus on HSE Criteria: A Case Study in the Oil and Gas Industry

2021 ◽  
Vol 6 (8) ◽  
pp. 105
Author(s):  
Assed N. Haddad ◽  
Bruno B. F. da Costa ◽  
Larissa S. de Andrade ◽  
Ahmed Hammad ◽  
Carlos A. P. Soares
Keyword(s):  
Supplier Selection ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Fuzzy Topsis ◽  
Topsis Method ◽  
Gas Industry ◽  
Selection Problems ◽  
Selection Processes ◽  
Level Of Importance

Supply chain management is an emerging topic in the oil and gas industry. There is higher exposure of contractors to undesirable incidents and supplier selection is a multicriteria decision problem (MCDM). A fuzzy-TOPSIS method was employed in the evaluation of three suppliers regarding four HSE criteria. This method was applied in a case study of the oil and gas industry involving a contractor bidding process. Results reinforced that fuzzy-TOPSIS is a versatile and suitable method for supplier selection problems, with low computational complexity and promoting a better user experience. This method contributes to greater effectiveness and agility in the selection processes of suppliers regarding HSE management. The fuzzy-TOPSIS model is suitable for supplier selection problems and some of the benefits of applying this method are that it allows the attribution weights according to the level of importance of each criterion and considers the complexity, subjectivity, and uncertainty of the decision process. One has determined that it was essential to have a robust and consistent process for weighting the criteria and defining the most appropriate linguistic variables.

A TODIM-Based Decision Support Framework for G-Resilient Supplier Selection in Fuzzy Environment

2016 ◽  
Vol 33 (05) ◽  
pp. 1650033 ◽  
Author(s):  
Dilip Kumar Sen ◽  
Saurav Datta ◽  
Siba Sankar Mahapatra
Keyword(s):  
Decision Support ◽  
Supplier Selection ◽  
Evaluation Criteria ◽  
Fuzzy Topsis ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision ◽  
Selection Problems ◽  
Fuzzy Environment ◽  
Decision Support Framework ◽  
Application Potential

A novel decision support framework has been proposed herein to solve supplier selection problems by considering green as well as resiliency criteria, simultaneously. In this work subjectivity of evaluation criteria has been tackled by exploring fuzzy set theory. A dominance based approach has been conceptualized which is basically a simplified version of TODIM. Application potential of the proposed dominance based fuzzy decision making approach has been compared to that of fuzzy-TOPSIS, fuzzy-VIKOR and also fuzzy-TODIM. The concept of a unique performance index, i.e. “g-resilient” index has been introduced here to help in assessing suppliers’ performance and thereby selecting the best candidate. The work has also been extended to identify the areas in which suppliers are lagging; these seek further improvement towards g-resilient suppliers’ performance to be boosted up to the desired level.

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