Consensus models for AHP group decision making under row geometric mean prioritization method

2010 ◽  
Vol 49 (3) ◽  
pp. 281-289 ◽  
Author(s):  
Yucheng Dong ◽  
Guiqing Zhang ◽  
Wei-Chiang Hong ◽  
Yinfeng Xu
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Geometric Mean ◽  
Prioritization Method ◽  
Consensus Models

How can a group of procurement experts select suppliers? An approach for group decision support

2014 ◽  
Vol 27 (4) ◽  
pp. 337-357 ◽  
Author(s):  
Arpan Kumar Kar ◽  
Ashis Kumar Pani
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Geometric Mean ◽  
Group Decision Support ◽  
Individual Decision ◽  
Individual Decision Making ◽  
Content Type

Purpose – The application of theories on group decision support is yet to be explored extensively in supplier selection literature, although the literature in both domains is extremely rich, in isolation. The purpose of this paper is to explore the application of group decision support theories for supplier selection. Design/methodology/approach – The row geometric mean method (RGMM) of the analytic hierarchy process (AHP) has been used in this study for the prioritization of group preferences under consensus. A case study was conducted to test the theories of consensual group decision making and compare it with other approaches based on AHP. Findings – The study establishes that the application of decision support theories for group decision making can improve the supplier selection process. Findings further imply that RGMM is more effective than eigen value method, for group decision making under consensus. Research limitations/implications – Methodologically, the study highlights the greater regularity in outcome of group decision making, vis-à-vis individual decision making, for the same decision-making context. Also, it highlights how RGMM is more effective since it preserves reciprocal properties and diversity in preferences better. Practical implications – The study establishes that firms can improve supplier selection processes by leveraging on the collective expertise of a group rather than depending on individual decision-making expertise. Originality/value – This study explores the application of different theories based on AHP for consensual group decision making. It compares different approaches based on AHP and establishes that RGMM is a superior approach for supplier selection.

Similarity-Based Approach for Group Decision Making with Multi-Granularity Linguistic Information

2016 ◽  
Vol 24 (06) ◽  
pp. 873-900 ◽  
Author(s):  
Jian Lin ◽  
Riqing Chen ◽  
Qiang Zhang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Geometric Mean ◽  
Multiple Sources ◽  
Linguistic Information ◽  
Trapezoidal Fuzzy Numbers ◽  
Attribute Weights ◽  
Linguistic Label

The aim of this article is to investigate the approach for multi-attribute group decision-making, in which the attribute values take the form of multi-granularity multiplicative linguistic information. Firstly, to process multiple sources of decision information assessed in different multiplicative linguistic label sets, a method for transforming multi-granularity multiplicative linguistic information into multiplicative trapezoidal fuzzy numbers is proposed. Then, a formula for ranking multiplicative trapezoidal fuzzy numbers is given based on geometric mean. Furthermore, the concept of similarity degree between two multiplicative trapezoidal fuzzy numbers is defined. The attribute weights are obtained by solving some optimization models. An effective approach for group decision making with multi-granularity multiplicative linguistic information is developed based on the ordered weighted geometric mean operator and proposed formulae. Finally, a practical example is provided to illustrate the practicality and validity of the proposed method.

EOWA AND EOWG OPERATORS FOR AGGREGATING LINGUISTIC LABELS BASED ON LINGUISTIC PREFERENCE RELATIONS

2004 ◽  
Vol 12 (06) ◽  
pp. 791-810 ◽  
Author(s):  
Z. S. XU
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Preference Relation ◽  
Geometric Mean ◽  
Weighted Averaging ◽  
Preference Relations ◽  
Ordered Weighted Averaging ◽  
Linguistic Preference Relation ◽  
Linguistic Labels

In this paper, we define two types of linguistic preference relations (multiplicative linguistic preference relation and additive linguistic preference relation), and study some of their desirable properties. We introduce the extended geometric mean (EGM) operator, extended arithmetical averaging (EAA) operator, extended ordered weighted averaging (EOWA) operator and extended ordered weighted geometric (EOWG) operator. An approach based on the EGM and EOWG operators and multiplicative linguistic preference relations and an approach based on the EAA and EOWA operators and additive linguistic preference relations are proposed to ranking the alternatives in the group decision-making problems. Finally, we give a numerical example to illustrate the developed approaches.

Soft Consensus Models in Group Decision Making

2016 ◽  
pp. 135-153
Author(s):  
Ignacio Javier Perez ◽  
Francisco Javier Cabrerizo ◽  
Sergio Alonso ◽  
Francisco Chiclana ◽  
Enrique Herrera-Viedma
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Consensus Models

scholarly journals Some Generalized Pythagorean Fuzzy Bonferroni Mean Aggregation Operators with Their Application to Multiattribute Group Decision-Making

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Runtong Zhang ◽  
Jun Wang ◽  
Xiaomin Zhu ◽  
Meimei Xia ◽  
Ming Yu
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Set ◽  
Group Decision ◽  
Geometric Mean ◽  
Intuitionistic Fuzzy Set ◽  
Aggregation Operators ◽  
Pythagorean Fuzzy Set ◽  
Bonferroni Mean ◽  
Novel Approach

The Pythagorean fuzzy set as an extension of the intuitionistic fuzzy set characterized by membership and nonmembership degrees has been introduced recently. Accordingly, the square sum of the membership and nonmembership degrees is a maximum of one. The Pythagorean fuzzy set has been previously applied to multiattribute group decision-making. This study develops a few aggregation operators for fusing the Pythagorean fuzzy information, and a novel approach to decision-making is introduced based on the proposed operators. First, we extend the generalized Bonferroni mean to the Pythagorean fuzzy environment and introduce the generalized Pythagorean fuzzy Bonferroni mean and the generalized Pythagorean fuzzy Bonferroni geometric mean. Second, a new generalization of the Bonferroni mean, namely, the dual generalized Bonferroni mean, is proposed by considering the shortcomings of the generalized Bonferroni mean. Furthermore, we investigate the dual generalized Bonferroni mean in the Pythagorean fuzzy sets and introduce the dual generalized Pythagorean fuzzy Bonferroni mean and dual generalized Pythagorean fuzzy Bonferroni geometric mean. Third, a novel approach to multiattribute group decision-making based on proposed operators is proposed. Lastly, a numerical instance is provided to illustrate the validity of the new approach.

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