Rough Number–Based Three-Way Group Decisions and Application in Influenza Emergency Management
- 10.2991/ijcis.d.190420.001How to use a DOI?
- Three-way decisions; Group decision-making; Rough numbers; Risk preference
Group decision-making can effectively deal with complex decision problems in reality and takes important research status in the field of decision-making. In recent years, three-way decision has been a hot topic in the field of uncertain decision-making, so the models of three-way decision under group environment have become a new direction and problem in decision-making research. Based on the subjectivity and uncertainty of the group judgment, this paper adopts the rough number method to objectively and effectively integrate the group information so as to establish rough number–based three-way decision models. First of all, we use rough numbers to transfer loss functions of individuals into a rough number–based gathering loss function, and verify the rough number–based loss function meets the general characteristics of general loss functions. Then from the perspectives of optimism, pessimism, risk preference of decision-makers, and directly operation of rough numbers, we explore the calculation of thresholds and the acquisition method of three-way rules, and then establish rough number–based three-way group decision models. Finally, influenza emergency management is introduced to verify the effectiveness and advancement of the novel method.
- © 2019 The Authors. Published by Atlantis Press SARL.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Fan Jia AU - Peide Liu PY - 2019 DA - 2019/04/26 TI - Rough Number–Based Three-Way Group Decisions and Application in Influenza Emergency Management JO - International Journal of Computational Intelligence Systems SP - 557 EP - 570 VL - 12 IS - 2 SN - 1875-6883 UR - https://doi.org/10.2991/ijcis.d.190420.001 DO - 10.2991/ijcis.d.190420.001 ID - Jia2019 ER -