A GMCDM approach with linguistic Z-numbers based on TOPSIS and Choquet integral considering risk preference

2020 ◽  
Vol 39 (3) ◽  
pp. 4285-4298
Author(s):  
Ran Tao ◽  
Fuyuan Xiao
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Choquet Integral ◽  
Risk Preference ◽  
Decision Makers ◽  
Multi Criteria Decision Making ◽  
Uncertain Information ◽  
Human Knowledge ◽  
Mcdm Method ◽  
Evaluation Information

Group multi-criteria decision-making (GMCDM) is an important part of decision theory, which is aimed to assess alternatives according to multiple criteria by collecting the wisdom of experts. However, in the process of evaluating, because of the limitation of human knowledge and the complexity of problems, an efficient GMCDM approach under uncertain environment still need to be further explored. Thus, in this paper, a novel GMCDM approach with linguistic Z-numbers based on TOPSIS and Choquet integral is proposed. Firstly, since linguistic Z-numbers performs better in coping with uncertain information, it is used to express the evaluation information. Secondly, TOPSIS, one of the most useful and systematic multi-criteria decision-making (MCDM) method, is adopted as the framework of the proposed approach. Thirdly, frequently it exists interaction between criteria, so Choquet integral is introduced to capture this kind of influence. What’s more, viewing that decision makers (DMs) show different preferences for uncertainty, the risk preference is regarded as a vital parameter when calculating the score of linguistic Z-numbers. An application in supplier selection is illustrated to demonstrate the effectiveness of the proposed approach. Finally, a further comparison and discussion of the proposed GMCDM method is given.

Supplier Selection Based on FAHP-VIKOR-IVIFs

2013 ◽  
Vol 357-360 ◽  
pp. 2703-2707 ◽  
Author(s):  
Hong Li Jiang ◽  
Hong Xing Yao
Keyword(s):  
Supplier Selection ◽  
Intuitionistic Fuzzy Sets ◽  
Information Environment ◽  
Decision Makers ◽  
Multi Criteria Decision Making ◽  
Uncertain Information ◽  
Vikor Method ◽  
Chain Management ◽  
Mcdm Method ◽  
Interval Valued

As the most important part of supply chain management, supplier selection has always received a great deal of attention from practitioners and researchers. However, the nature of supplier selection is a complex multi-criteria decision making (MCDM) problem including many factors which may be in conflict. VIKOR is an efficient method to solve this kind of MCDM problem. But in reality, there usually exists incomplete and uncertain information, and the decision makers cannot easily express their judgments on the alternatives with exact and crisp values. Therefore, a new extended VIKOR method with interval-valued intuitionistic fuzzy sets (IVIF-VIKOR) is proposed in this paper. Then a hybrid MCDM method based on FAHP and the proposed IVIF-VIKOR are used to select supplier under incomplete and uncertain information environment. The feasibility and practicability of FAHP-IVIF-VIKOR method are further manifested through an empirical example.

A Multi-Criteria Intuitionistic Fuzzy Group Decision Making Method for Supplier Selection with VIKOR Method

2012 ◽  
pp. 967-983
Author(s):  
Razieh Roostaee ◽  
Mohammad Izadikhah ◽  
Farhad Hosseinzadeh Lotfi ◽  
Mohsen Rostamy-Malkhalifeh
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Decision Makers ◽  
Uncertain Information ◽  
Vikor Method ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
The Right

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.

A Multi-Criteria Intuitionistic Fuzzy Group Decision Making Method for Supplier Selection with VIKOR Method

2012 ◽  
Vol 2 (1) ◽  
pp. 1-17 ◽  
Author(s):  
Razieh Roostaee ◽  
Mohammad Izadikhah ◽  
Farhad Hosseinzadeh Lotfi ◽  
Mohsen Rostamy-Malkhalifeh
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Decision Makers ◽  
Uncertain Information ◽  
Vikor Method ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
The Right

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.

scholarly journals AN EXTENDED TODIM METHOD FOR PROJECT MANAGER’S COMPETENCY EVALUATION

2019 ◽  
Vol 25 (7) ◽  
pp. 673-686 ◽  
Author(s):  
Jielin Yin ◽  
Jian Guo ◽  
Tianmeng Ji ◽  
Jingru Cai ◽  
Lei Xiao ◽  
...  
Keyword(s):  
Decision Making ◽  
High Efficiency ◽  
Choquet Integral ◽  
Project Managers ◽  
Project Manager ◽  
Decision Makers ◽  
Multi Criteria Decision Making ◽  
Psychological Behavior ◽  
Todim Method ◽  
Competency Evaluation

The project managers’ high efficiency and leadership ability is very important for the success of the whole project. Evaluating the competency of project manager accurately and selecting the suitable project manager from alternatives is a very core research issue that should be paid high attention to in the field of project management. When evaluating the competency of project manager, multiple criteria with interactive relationship should be considered, and the decision makers may have bounded rational behavior which may have a great impact on the result of evaluation, whereas the decision makes’ psychological behavior is rarely taken into account in the existing studies on the evaluation of project managers’ competency. TODIM (an acronym in Portuguese of interactive and multi-criteria decision making) is a multi-criteria decision making method considering the decision makers’ behavior. In this paper, an extended TODIM method which combines λ -fuzzy measure with Choquet integral considering incomplete criteria information and decision makers’ bounded rational behaviors are presented to evaluate the competency of project manager. Furthermore, a numerical example is presented to illustrate the method proposed. We hope that this method can provide some valuable references for the evaluation of project manager’s competency.

Projection-based probabilistic linguistic multi-criteria decision-making method for new energy project selection

2021 ◽  
pp. 1-16
Author(s):  
Min-Hui Deng ◽  
Xiao-Yu Zhou ◽  
Jian-Qiang Wang ◽  
Jun-Bo Li ◽  
Peng-Fei Cheng
Keyword(s):  
Decision Making ◽  
Numerical Study ◽  
Project Selection ◽  
Decision Makers ◽  
Maximum Deviation ◽  
Multi Criteria Decision Making ◽  
Uncertain Information ◽  
Projection Model ◽  
Energy Projects ◽  
New Energy

The development of new energy industry is a pressing issue due to the deterioration of the environment. The selection of new energy projects is a critical problem for decision makers. Incomplete and uncertain information appears in the process of new energy project selection. Compared with other linguistic expressions, probabilistic linguistic term set (PLTS) simultaneously reflects all possible linguistic terms and their corresponding weights, which conforms to the cognitive habits of people. Thus, a multi-criteria decision-making framework under PLTS environment is constructed for energy project selection. Firstly, a normalised projection model of PLTS, which considers the distance and the angle between two objects, is proposed to overcome the limitations of distance measurement. Secondly, a comprehensive weight-determination method combining the maximum deviation and expert scoring methods is developed to calculate the weight vector of the criteria. Furthermore, a projection-based VIKOR (Višekriterijumska optimizacija i kompromisno rešenje) method is established to select new energy projects, which can reflect the preferences of decision makers for group utility and individual regret. Finally, a numerical study on new energy project selection is performed to determine the validity and applicability of this method. Sensitive and comparative analyses are also conducted to reflect the rationality and feasibility of the method.

scholarly journals NEW DISSIMILARITY MEASURES ON PICTURE FUZZY SETS AND APPLICATIONS

2018 ◽  
Vol 34 (3) ◽  
pp. 219-231 ◽  
Author(s):  
Nhung Thi Le ◽  
Dinh Van Nguyen ◽  
Chau Minh Ngoc ◽  
Thao Xuan Nguyen
Keyword(s):  
Decision Making ◽  
Pattern Recognition ◽  
Fuzzy Sets ◽  
Supplier Selection ◽  
Intuitionistic Fuzzy Sets ◽  
Multi Criteria Decision Making ◽  
Dissimilarity Measures ◽  
Selection Problems ◽  
Mcdm Method ◽  
Picture Fuzzy Sets

The dissimilarity measures between fuzzy sets/intuitionistic fuzzy sets/picture fuzzy sets are studied and applied in various matters. In this paper, we propose some new dissimilarity measures on picture fuzzy sets. This new dissimilarity measures overcome the restrictions of all existing dissimilarity measures on picture fuzzy sets. After that, we apply these new measures to the pattern recognition problems. Finally, we introduce a multi-criteria decision making (MCDM) method that used the new dissimilarity measures and apply them in the supplier selection problems.

scholarly journals Multi-Criteria Decision Making and its Applications

2019 ◽  
Vol 8 (9S4) ◽  
pp. 149-153
Keyword(s):  
Decision Making ◽  
Basic Principle ◽  
Decision Makers ◽  
Multi Criteria Decision Making ◽  
Operational Model ◽  
Criteria Weights ◽  
Working Principle ◽  
Mcdm Method ◽  
Application Fields ◽  
Selection Of

Multi-criteria decision making (MCDM) is a powerful operational model which are used to resolve decision making problems on the basis of different decision criteria. This approach has been widely used in many application fields by the decision makers to solve their problems. Although there exists different MCDM methods but the basic principle of MCDM method involves selection of criteria, selection of alternatives, selection of aggregation methods and weight criteria using these methods and finally evaluation of a set of alternatives performed based on criteria weights. This study presents a small description on the working principle and different methods of a Multi-criteria decision making and furthermore provides survey on their application in different fields.

CPT-MABAC method for spherical fuzzy multiple attribute group decision making and its application to green supplier selection

2021 ◽  
pp. 1-11
Author(s):  
Huiyuan Zhang ◽  
Guiwu Wei ◽  
Xudong Chen
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Comparison Method ◽  
Entropy Method ◽  
Decision Makers ◽  
Green Supplier Selection ◽  
Multiple Attribute ◽  
Psychological Perceptions

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.

Sign in / Sign up

Export Citation Format

Share Document