Supplier selection method based on group decision making problems with alternative preference information in form of ordinal interval

Author(s):  
Zhang Enyuan ◽  
Zhang Bin
2013 ◽  
Vol 357-360 ◽  
pp. 2730-2737 ◽  
Author(s):  
Jun Ling Zhang ◽  
Xiao Wen Qi ◽  
Hai Bin Huang

This paper investigates multiple attribute group decision making (MAGDM) with hesitant fuzzy preference information, which is a significantly import issue to be deeply studied in management and industrial engineering. Firstly, simultaneously considering optimistic and pessimistic attitudinal preference information, an improved distance measure for hesitant fuzzy set is defined. Then, utilizing the newly defined distance measure, a hesitant fuzzy multiple attribute group decision making approach based on TOPSIS method is constructed, which can effectively avoid high complexity of aggregating hesitant fuzzy information in traditional methods. Further, an application study on parts supplier selection has verified the practically and effectiveness of developed methods.


2021 ◽  
pp. 1-11
Author(s):  
Huiyuan Zhang ◽  
Guiwu Wei ◽  
Xudong Chen

The green supplier selection is one of the popular multiple attribute group decision making (MAGDM) problems. The spherical fuzzy sets (SFSs) can fully express the complexity and fuzziness of evaluation information for green supplier selection. Furthermore, the classic MABAC (multi-attributive border approximation area comparison) method based on the cumulative prospect theory (CPT-MABAC) is designed, which is an optional method in reflecting the psychological perceptions of decision makers (DMs). Therefore, in this article, we propose a spherical fuzzy CPT-MABAC (SF-CPT-MABAC) method for MAGDM issues. Meanwhile, considering the different preferences of DMs to attribute sets, we obtain the objective weights of attributes through entropy method. Focusing on the current popular problems, this paper applies the proposed method for green supplier selection and proves for green supplier selection based on SF-CPT-MABAC method. Finally, by comparing existing methods, the effectiveness of the proposed method is certified.


2014 ◽  
Vol 13 (05) ◽  
pp. 979-1012 ◽  
Author(s):  
Ting-Yu Chen

Interval type-2 fuzzy sets (T2FSs) with interval membership grades are suitable for dealing with imprecision or uncertainties in many real-world problems. In the Interval type-2 fuzzy context, the aim of this paper is to develop an interactive signed distance-based simple additive weighting (SAW) method for solving multiple criteria group decision-making problems with linguistic ratings and incomplete preference information. This paper first formulates a group decision-making problem with uncertain linguistic variables and their transformation to interval type-2 trapezoidal fuzzy numbers. Concerning the relative importance of multiple decision-makers and group consensus of fuzzy opinions, a procedure using hybrid averages is then employed to construct a collective decision matrix. By an appropriate extension of the classical SAW approach, this paper utilizes the concept of signed distances and establishes an integrated programming model to manage multi-criteria group decisions under the incomplete and inconsistent preference structure. Further, an interactive procedure is established for group decision making. Finally, the feasibility and effectiveness of the proposed methods are illustrated by a collaborative decision-making problem of patient-centered care (PCC).


Symmetry ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 505 ◽  
Author(s):  
Zengxian Li ◽  
Guiwu Wei ◽  
Mao Lu

In this paper, we extend the Hamy mean (HM) operator and dual Hamy mean (DHM) operator with Pythagorean fuzzy numbers (PFNs) to propose Pythagorean fuzzy Hamy mean (PFHM) operator, weighted Pythagorean fuzzy Hamy mean (WPFHM) operator, Pythagorean fuzzy dual Hamy mean (PFDHM) operator, weighted Pythagorean fuzzy dual Hamy mean (WPFDHM) operator. Then the multiple attribute group decision making (MAGDM) methods are proposed with these operators. In the end, we utilize an applicable example for supplier selection to prove the proposed methods.


2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Muhammad Naeem ◽  
Muhammad Qiyas ◽  
Saleem Abdullah

With respect to multiple criteria group decision-making (MCGDM) problems in which both the criteria weights and the expert weights take the form of crisp numbers and attribute values take the form of interval-valued picture fuzzy uncertain linguistic numbers, some new group decision-making analysis methods are developed. Firstly, some operational laws, expected value, and accuracy function of interval-valued picture fuzzy uncertain linguistic numbers are introduced. Then, an interval-valued picture fuzzy uncertain linguistic averaging and geometric aggregation operators are developed. Furthermore, some desirable properties of the developed operators, such as commutativity, idempotency, and monotonicity, have been studied. Based on these operators, an approach to multiple criteria group decision-making with interval-valued picture fuzzy uncertain linguistic information has been proposed. Finally, a practical example of 3PL supplier selection in logistics service value concretion is taken to test the defined method and to expose the effectiveness of the defined model.


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.


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