Expected consistency-based model and multiplicative DEA cross-efficiency for group decision-making with incomplete distribution linguistic preference relations

2021 ◽  
pp. 1-21
Author(s):  
Jinpei Liu ◽  
Longlong Shao ◽  
Ligang Zhou ◽  
Feifei Jin
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Optimization Model ◽  
Group Decision ◽  
Preference Relation ◽  
Preference Relations ◽  
Priority Vector ◽  
Linguistic Preference Relation ◽  
Multiplicative Preference Relations ◽  
High Consistency

Faced with complex decision problems, Distribution linguistic preference relation (DLPR) is an effective way for decision-makers (DMs) to express preference information. However, due to the complexity of the decision-making environment, DMs may not be able to provide complete linguistic distribution for all linguistic terms in DLPRs, which results in incomplete DLPRs. Therefore, in order to solve group decision-making (GDM) with incomplete DLPRs, this paper proposes expected consistency-based model and multiplicative DEA cross-efficiency. For a given incomplete DLPRs, we first propose an optimization model to obtain complete DLPR. This optimization model can evaluate the missing linguistic distribution and ensure that the obtained DLPR has a high consistency level. And then, we develop a transformation function that can transform DLPRs into multiplicative preference relations (MPRs). Furthermore, we design an improved multiplicative DEA model to obtain the priority vector of MPR for ranking all alternatives. Finally, a numerical example is provided to show the rationality and applicability of the proposed GDM method.

AN APPROACH TO GROUP DECISION MAKING BASED ON INCOMPLETE LINGUISTIC PREFERENCE RELATIONS

2005 ◽  
Vol 04 (01) ◽  
pp. 153-160 ◽  
Author(s):  
ZESHUI XU
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Preference Relation ◽  
Linguistic Variables ◽  
Preference Relations ◽  
Weighted Arithmetic ◽  
Operational Laws ◽  
Linguistic Preference Relation

In this paper, we introduce some operational laws of linguistic variables and define some linguistic preference relations such as incomplete linguistic preference relation and improved linguistic preference relation, etc. We then utilize the extended arithmetic averaging (EAA) operator and the extended weighted arithmetic averaging (EWAA) operator to develop an approach to group decision making based on incomplete linguistic preference relations. Finally, we give an illustrative example to verify the developed approach.

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.

ON COMPATIBILITY OF UNCERTAIN MULTIPLICATIVE LINGUISTIC PREFERENCE RELATIONS AND ITS APPLICATION TO GROUP DECISION MAKING

2013 ◽  
Vol 21 (01) ◽  
pp. 9-28 ◽  
Author(s):  
LIGANG ZHOU ◽  
HUAYOU CHEN
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Preference Relation ◽  
Scientific Basis ◽  
Decision Makers ◽  
Preference Relations ◽  
Compatibility Index ◽  
Optimal Weights ◽  
Linguistic Preference Relation

The aim of this work is to develop a new compatibility for the uncertain multiplicative linguistic preference relations and determine the optimal weights of decision makers (DMs), which are very suitable to deal with group decision making (GDM) problems involving uncertain multiplicative linguistic preference relations. First, the concepts of compatibility degree and compatibility index for the two uncertain multiplicative linguistic preference relations are proposed. Then we prove the property that the synthetic uncertain linguistic preference relation is of acceptable compatibility under the condition that uncertain multiplicative linguistic preference relations given by DMs are all of acceptable compatibility with a specific linguistic preference relation, which is the scientific basis of using the uncertain multiplicative linguistic preference relations in the GDM. Next, in order to determine the weights of decision makers, we construct an optimal model based on the criterion of minimizing the compatibility index. Finally, we develop an application of the optimal weights approach compared with the equal weights approach where we analyze a GDM regarding the selection of investment.

A Novel Algorithm for Group Decision Making Based on Continuous Optimal Aggregation Operator and Shapley Value

2019 ◽  
Vol 27 (06) ◽  
pp. 969-1002
Author(s):  
Jian Lin ◽  
Qiang Zhang ◽  
Fanyong Meng
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Preference Relation ◽  
Aggregation Operator ◽  
Fuzzy Measure ◽  
Chi Square ◽  
Preference Relations ◽  
Special Cases ◽  
Linguistic Preference Relation

Interval linguistic preference relation is an effective tool for expressing experts’ preference in group decision making under uncertain linguistic environment. A new aggregation operator called continuous chi-square deviation based 2-tuple linguistic ordered weighted quasi-averaging (C-CDLOWQ) operator is proposed to transform the interval linguistic preference relations into precise linguistic preference relations. Some desirable properties and special cases of the C-CDLOWQ operator are analyzed in detail. To take the interactive phenomenon among experts into account, the Shapley weighting vector is presented to integrate the expected linguistic preference relations. The λ-fuzzy measure is employed to simplify the fuzzy measure on expert set. A CS-GDM algorithm is developed to group decision making with interval linguistic preference relations. The application in commercial investment problem is provided to illustrate the effectiveness of CS-GDM algorithm.

scholarly journals A Method Adjusting Consistency and Consensus for Group Decision-Making Problems with Hesitant Fuzzy Linguistic Preference Relations Based on Discrete Fuzzy Numbers

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Meng Zhao ◽  
Ting Liu ◽  
Jia Su ◽  
Meng-Ying Liu
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Preference Relation ◽  
Feedback Mechanism ◽  
Preference Relations ◽  
Linguistic Preference Relation ◽  
Consensus Reaching Process ◽  
Fuzzy Linguistic

In each hesitant fuzzy linguistic preference relation, experts may express their opinions through comparison linguistic information combined with a discrete fuzzy number. In this paper, a hesitant fuzzy linguistic computational model based on discrete fuzzy numbers whose support is a subset of consecutive natural numbers is proposed, which enriches the flexibility of group decision-making. First, some main concepts related to discrete fuzzy numbers and an aggregation function of individual subjective linguistic preference relations are introduced. Then, a consistency measure is presented to check and improve the consistency in a given matrix. Further, in order to achieve the predefined degree of consensus and to arrive at the final result, a consensus-reaching process based on the interactive feedback mechanism is defined. Meanwhile, a revised formula is introduced to calculate the consistency and the degree of consensus in a preference relation matrix. Besides, an illustrative example and comparative analysis are conducted through the proposed calculation process and the optimization algorithm. Finally, the analysis on the threshold values is made to help the decision-maker determine critical consensus level. The proposed method can address both consistency and consensus, and the results confirmed the effectiveness of the proposed method and its potential use in the qualitative decision-making problems.

scholarly journals Additively Consistent Interval-Valued Intuitionistic Fuzzy Preference Relations and Their Application to Group Decision Making

Information ◽  
2018 ◽  
Vol 9 (10) ◽  
pp. 260 ◽  
Author(s):  
Hua Zhuang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Preference Relation ◽  
Weighted Averaging ◽  
Preference Relations ◽  
Intuitionistic Fuzzy ◽  
Priority Weights ◽  
Interval Valued ◽  
Fuzzy Preference

This paper aims to propose an innovative approach to group decision making (GDM) with interval-valued intuitionistic fuzzy (IVIF) preference relations (IVIFPRs). First, an IVIFPR is proposed based on the additive consistency of an interval-valued fuzzy preference relation (IVFPR). Then, two mathematical or adjusted programming models are established to extract two special consistent IVFPRs. In order to derive the priority weight of an IVIFPR, after taking the two special IVFPRs into consideration, a linear optimization model is constructed by minimizing the deviations between individual judgments and between the width degrees of the interval priority weights. For GDM with IVIFPRs, the decision makers’ weights are generated by combining the adjusted subjective weights with the objective weights. Subsequently, using an IVIF-weighted averaging operator, the collective IVIFPR is obtained and utilized to derive the IVIF priority weights. Finally, a practical example of a supplier selection is analyzed to demonstrate the application of the proposed method.

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