Analysis of self-confidence indices-based additive consistency for fuzzy preference relations with self-confidence and its application in group decision making

2018 ◽  
Vol 34 (5) ◽  
pp. 920-946 ◽  
Author(s):  
Xia Liu ◽  
Yejun Xu ◽  
Rosana Montes ◽  
Yucheng Dong ◽  
Francisco Herrera
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Preference Relations ◽  
Additive Consistency ◽  
Self Confidence ◽  
Fuzzy Preference Relations ◽  
Fuzzy Preference

A Natural Method for Ranking Objects from Hesitant Fuzzy Preference Relations

2017 ◽  
Vol 16 (06) ◽  
pp. 1611-1646 ◽  
Author(s):  
Jie Tang ◽  
Qingxian An ◽  
Fanyong Meng ◽  
Xiaohong Chen
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Group Consensus ◽  
Preference Relations ◽  
Additive Consistency ◽  
Mixed Programming ◽  
Fuzzy Preference Relations ◽  
Fuzzy Preference

Hesitant fuzzy preference relations (HFPRs) are efficient tools to denoting the decision maker’s judgements that permit the decision makers to compare objects using several values in [0, 1], and the number of elements in different hesitant fuzzy elements may be different. After reviewing the previous researches about decision making with HFPRs, one can find that there are several limitations. To avoid these issues and to guarantee the reasonable ranking order, this paper introduces a new additive consistency concept for HFPRs. Different from the previous consistency concepts, the new concept neither needs to add values into hesitant fuzzy elements nor disregards any information offered by the decision makers. To measure the additive consistency of HFPRs, two 0-1 mixed programming models are constructed. Meanwhile, an additive consistency based 0-1 mixed programming model is established to determining the missing values in incomplete HFPRs that can address the situation where ignored objects exist. Then, an algorithm to obtaining the hesitant fuzzy priority weight vector from (incomplete) HFPRs is provided. Considering group decision making, a new group consensus index is defined, and an interactive approach to improving the group consensus level of individual HFPRs is offered. Furthermore, a probability distance measure between two HFPRs is defined to deriving the weights of the decision makers. According to the additive consistency and consensus analysis, an approach to group decision making with incomplete and inconsistent HFPRs is performed. Finally, two practical numerical examples are provided, and comparison analysis is offered.

scholarly journals A Group Decision Making Approach Considering Self-confidence Behaviors and Its Application in Environmental Pollution Emergency Management

2019 ◽  
Vol 16 (3) ◽  
pp. 385 ◽  
Author(s):  
Xia Liu ◽  
Yejun Xu ◽  
Yao Ge ◽  
Weike Zhang ◽  
Francisco Herrera
Keyword(s):  
Decision Making ◽  
Environmental Pollution ◽  
Emergency Management ◽  
Group Decision Making ◽  
Group Decision ◽  
The Self ◽  
Preference Relations ◽  
Self Confidence ◽  
Fuzzy Preference Relations ◽  
Fuzzy Preference

Self-confidence as one of the human psychological behaviors has important influence on emergency management decision making, which has been ignored in existing methods. To fill this gap, we dedicate to design a group decision making approach considering self-confidence behaviors and apply it to the environmental pollution emergency management. In the proposed method, the self-confident fuzzy preference relations are utilized to express experts’ evaluations. This new type of preference relations allow experts to express multiple self-confidence levels when providing their evaluations, which can deal with the self-confidence of them well. To apply the proposed group decision making method to environmental pollution emergency management, a novel determination of the decision weights of experts is given combining the subjective and objective weights. The subjective weight can be directly assigned by organizer, while the objective weight is determined by the self-confidence degree of experts on their evaluations. Afterwards, by utilizing the weighted averaging operator, the individuals’ evaluations can be aggregated into a collective one. To do that, some operational laws for self-confident fuzzy preference relations are introduced. And then, a self-confidence score function is designed to get the best solution for environmental pollution emergency management. Finally, some analyses and discussions show that the proposed method is feasible and effective.

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