Consistency and consensus modeling of linear uncertain preference relations

Gong, Zaiwu; Guo, Weiwei; Herrera‐Viedma, Enrique; Gong, Zejun; Wei, Guo

doi:10.1016/j.ejor.2019.10.035

Cited by 102 publications

(20 citation statements)

References 59 publications

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“…If we consider the maximum absolute differences to be a minimized problem with the same compromise limit constraints, then the priority weight vectors of the criteria are obtained from Eqs. ( 9), ( 10) and (11); otherwise, if we consider the maximum absolute differences to be a minimized problem with different compromise limit constraints, the priority weight vectors of the criteria are obtained from Eqs. (10), ( 11) and (13).…”

Section: A Framework Of Mcdm Procedures Based On Hesitant Fuzzy Bwmmentioning

confidence: 99%

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Approaches for multicriteria decision-making based on the hesitant fuzzy best–worst method

Niu

Chen

et al. 2021

Complex Intell. Syst.

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Hesitant fuzzy preference relations (HFPRs) have been widely applied in multicriteria decision-making (MCDM) for their ability to efficiently express hesitant information. To address the situation where HFPRs are necessary, this paper develops several decision-making models integrating HFPRs with the best worst method (BWM). First, consistency measures from the perspectives of additive/multiplicative consistent hesitant fuzzy best worst preference relations (HFBWPRs) are introduced. Second, several decision-making models are developed in view of the proposed additive/multiplicatively consistent HFBWPRs. The main characteristic of the constructed models is that they consider all the values included in the HFBWPRs and consider the same and different compromise limit constraints. Third, an absolute programming model is developed to obtain the decision-makers’ objective weights utilizing the information of optimal priority weight vectors and provides the calculation of decision-makers’ comprehensive weights. Finally, a framework of the MCDM procedure based on hesitant fuzzy BWM is introduced, and an illustrative example in conjunction with comparative analysis is provided to demonstrate the feasibility and efficiency of the proposed models.

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Section: A Framework Of Mcdm Procedures Based On Hesitant Fuzzy Bwmmentioning

confidence: 99%

“…For MPRs, Saaty [6] defined the concept of multiplicatively consistent MPRs, which indicates the multiplicative transitivity among three related comparisons. Since then, MCDM approaches based on two types of PRs have been proposed [7][8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Approaches for multicriteria decision-making based on the hesitant fuzzy best–worst method

Niu

Chen

et al. 2021

Complex Intell. Syst.

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“…DMs’ social experience and cultural background, however, can lead to conflicts arising among them. In this situation, the application of a consensus reaching processes in LSGDM to build consensual opinions was successfully applied (Gong et al 2020a , b ). Therefore, consensus reaching process (CRP) is a key stage in the process of obtaining an acceptable solution for all DMs.…”

Section: Introductionmentioning

confidence: 99%

“…The large number of experts involved in LSGDM problems will inevitably lead to a large number of assessments, which can be utilized to deduce valuable decision-making information with statistical inference (Gong et al 2020a ; Ma et al 2020 ). To put this in context, we note that with respect to group evaluation problems, Bu ( 2007 ) introduced a parameter estimation method with statistical inference theory and the AHP method, and developed a mathematical model to derive efficient and practical GDM results.…”

Section: Introductionmentioning

confidence: 99%

Consensus-Based Linguistic Distribution Large-Scale Group Decision Making Using Statistical Inference and Regret Theory

et al. 2021

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“…Generally, preference changing are associated a cost and the resources for consensus building are limited (Ben-Arieh and Easton 2007;Dong et al 2010Dong et al , 2015Dong and Xu 2016;Gong et al 2017Gong et al , 2019Tan et al 2018). Based on these premises, some CRPs with MCC have been developed (Ben-Arieh and Easton 2007;Ben-Arieh et al 2008;Cheng et al 2018;Gong et al 2015a, b;Zhang et al 2017Zhang et al , 2019b.…”

Section: Introductionmentioning

confidence: 99%

Impact of Decision Rules and Non-cooperative Behaviors on Minimum Consensus Cost in Group Decision Making

et al. 2020

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In group decision making, it is sensible to achive minimum consensus cost (MCC) because the consensus reaching process resources are often limited. In this endeavour, though, there are still two issues that require paying attention to: (1) the impact of decision rules, including decision weights and aggregation functions, on MCC; and (2) the impact of non-cooperative behaviors on MCC. Hence, this paper analytically reveals the decision rules to minimize MCC or maximize MCC. Furthermore, detailed simulation experiments show the joint impact of non-cooperative behavior and decisions rules on MCC, as well as revealing the effect of the consensus within the established MCC target.

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Consistency and consensus modeling of linear uncertain preference relations

Cited by 102 publications

References 59 publications

Approaches for multicriteria decision-making based on the hesitant fuzzy best–worst method

Approaches for multicriteria decision-making based on the hesitant fuzzy best–worst method

Consensus-Based Linguistic Distribution Large-Scale Group Decision Making Using Statistical Inference and Regret Theory

Impact of Decision Rules and Non-cooperative Behaviors on Minimum Consensus Cost in Group Decision Making

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