Abstract
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.
Highlights
Group decision making (GDM) refers to a condition whereby a group of experts are involved in a decision process, provide their evaluations regarding the provided alternatives, and select an optimal decision by the aggregation of their opinions [1]
For a collective self-confident fuzzy preference relation (SC-FPR), we propose to choose the best alternative by computing the self-confidence score function (SCS) of each alternative
To improve the quality of emergency management decisions, this paper focuses on the GDM
Summary
Self-Confidence Behaviors and Its Application in Environmental Pollution Emergency Management. Xia Liu 1,2 , Yejun Xu 1 , Yao Ge 3, *, Weike Zhang 2,3 and Francisco Herrera 2,4. Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia. Received: 1 December 2018; Accepted: 25 January 2019; Published: 29 January 2019
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