A review of soft consensus models in a fuzzy environment |
| |
| Affiliation: | 1. PRESAD Research Group and Multidisciplinary Institute of Enterprise (IME), Faculty of Sciences University of Valladolid, Valladolid, Spain;2. BORDA Research Unit, PRESAD Research Group and Multidisciplinary Institute of Enterprise (IME), University of Salamanca, Salamanca, Spain;3. Centre for Computational Intelligence, School of Computer Science and Informatics, Faculty of Technology, De Montfort University, Leicester, UK;1. Business School, Sichuan University, Chengdu, 610065, China;2. Department of Computer Science and Artificial Intelligence, University of Granada, Granada, 18071, Spain;3. Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, 21589, Saudi Arabia |
| |
| Abstract: | In the consensus reaching processes developed in group decision making problems we need to measure the closeness among experts’ opinions in order to obtain a consensus degree. As it is known, to achieve a full and unanimous consensus is often not reachable in practice. An alternative approach is to use softer consensus measures, which reflect better all possible partial agreements, guiding the consensus process until high agreement is achieved among individuals. Consensus models based on soft consensus measures have been widely used because these measures represent better the human perception of the essence of consensus. This paper presents an overview of consensus models based on soft consensus measures, showing the pioneering and prominent papers, the main existing approaches and the new trends and challenges. |
| |
| Keywords: | Group decision making Consensus Soft consensus measures Fuzzy logic |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
