scholarly journals Supplier Selection Problem Based on Interval Intuitionistic Fuzzy Multiattribute Group Decision Making

2019 ◽  
Vol 07 (03) ◽  
pp. 1494-1503
Author(s):  
Danyi Song ◽  
Jiao Wang
Author(s):  
Mohammad Azadfallah

Some authors implicitly claim that in the TOPSIS and Bordas function approach, each expert may or may not be using the same criteria. Meanwhile, in our reviews of the literature, not any reference was found that deals with supplier selection problem in the conditions each expert have own criteria set. So, the application of a Multiple Attribute Group Decision Making (MAGDM) model, particularly TOPSIS and Boards function approach for solving an supplier selection problem, while, each expert have own criteria set is the aim of this paper. Finally, a simple example is provided in order to demonstrate its feasibility and practicability of the proposed method.


2012 ◽  
pp. 967-983
Author(s):  
Razieh Roostaee ◽  
Mohammad Izadikhah ◽  
Farhad Hosseinzadeh Lotfi ◽  
Mohsen Rostamy-Malkhalifeh

Supplier selection, the process of finding the right suppliers who are able to provide the buyer with the right quality products and/or services at the right price, at the right time and in the right quantities, is one of the most critical activities for establishing an effective supply chain, and is typically a multi-criteria group decision problem. In many practical situations, there usually exists incomplete and uncertain information, and the decision makers cannot easily express their judgments on the candidates with exact and crisp values. Therefore, in this paper an extended VIKOR method for group decision making with intuitionistic fuzzy numbers is proposed to solve the supplier selection problem under incomplete and uncertain information environment. In other researches in this area, the weights of each decision makers and in many of them the weights of criteria are pre-determined, but these weights have been calculated in this paper by using the decision matrix of each decision maker. Also, normalized Hamming distance is proposed to calculate the distance between intuitionistic fuzzy numbers. Finally, a numerical example for supplier selection is given to clarify the main results developed in this paper.


2021 ◽  
Author(s):  
Chong Wu ◽  
Haohui Zou ◽  
David Barnes

Abstract With the recent emphasis on supply risk management in sustainable supply chains (SSCs), the evaluation and selection of appropriate suppliers are more important than ever. However, most existing research does not take all three sustainability perspectives of supply risk into account simultaneously and they rarely consider the correlation among supply risk factors in risk assessment. Therefore, considering the uncertain information decision-making environment, this research paper proposes a risk-based integrated group decision-making model for sustainable supplier selection (SSS). First, the weights of decision-makers (DMs) are taken as linguistic terms denoted by intuitionistic fuzzy numbers (IFNs). Second, after obtaining the aggregated intuitionistic fuzzy decision-making matrix considering the expert weights, this study uses the entropy weight method to calculate the criteria weights objectively. Then, the improved failure mode and effects analysis (FMEA) is adopted for the risk assessment to exclude high-risk suppliers. Finally, the extended alternative queuing method (AQM) is applied to rank the qualified suppliers in SSCs. This model can not only enable enterprises to reduce supply risk in SSS practices and identify and prevent the failure modes that lead to supply risk, but also reduce the uncertainty of decision-making, in order to make supplier selection more accurate. The feasibility and effectiveness of the proposed model are illustrated through application in a leading Chinese electrical appliance manufacturing company.


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