Elsevier

Applied Soft Computing

Volume 99, February 2021, 106879
Applied Soft Computing

A consensus model to manage the non-cooperative behaviors of individuals in uncertain group decision making problems during the COVID-19 outbreak

https://doi.org/10.1016/j.asoc.2020.106879Get rights and content

Highlights

  • We propose a consensus model to supervise and manage non-cooperative behaviors.

  • Experts are classified based on similarities of preferences and cooperation degrees.

  • A dynamic weight punishment mechanism is proposed for non-cooperative experts.

Abstract

The COVID-19 pandemic has brought lots of losses to the global economy. Within the context of COVID-19 outbreak, many emergency decision-making problems with uncertain information arose and a number of individuals were involved to solve such complicated problems. For instance, the selection of the first entry point to China is important for oversea flights during the epidemic outbreak given that reducing imported virus from abroad becomes the top priority of China since China has achieved remarkable achievements regarding the epidemic control. In such a large-scale group decision making problem, the non-cooperative behaviors of experts are common due to the different backgrounds of the experts. The non-cooperative behaviors of experts have a negative impact on the efficiency of a decision-making process in terms of decision time and cost. Given that the non-cooperative behaviors of experts were rarely considered in existing large-scale group decision making methods, this study aims to propose a novel consensus model to manage the non-cooperative behaviors of experts in large-scale group decision making problems. A group consistency index simultaneously considering fuzzy preference values and cooperation degrees is introduced to detect the non-cooperative behaviors of experts. We combine the cooperation degrees and fuzzy preference similarities of experts when clustering experts. To reduce the negative influence of the experts with low degrees of cooperation on the quality of a decision-making process, we implement a dynamic weight punishment mechanism to non-cooperative experts so as to improve the consensus level of a group. An illustrative example about the selection of the first point of entry for the flights entering Beijing from Toronto during the COVID-19 outbreak is presented to show the validity of the proposed model.

Keywords

COVID-19 outbreak
Group decision making
Non-cooperative behaviors
Consensus model
Fuzzy preference relations
Cooperative behavior relations

Cited by (0)

View Abstract