Improving consistency in fuzzy preference relations with an allocation of information granularity

Date

2014-09

Advisors

Journal Title

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ISSN

DOI

Volume Title

Publisher

IOS Press

Type

Book chapter

Peer reviewed

Yes

Abstract

An important issue to bear in mind in Group Decision Making situations is that of consistency. However, the expression of consistent preferences is often a very difficult task for the decision makers, specially in decision problems with a high number of alternatives and when decision makers use fuzzy preference relations to provide their opinions. It leads to situations where a decision maker may not be able to express all his/her preferences properly and without contradiction. To overcome this problem, we propose the concept of the information granularity being regarded as an important and useful asset supporting the goal to reach consistent fuzzy preference relations. To do so, we develop a concept of granular fuzzy preference relation where each pairwise comparison is formed as a certain information granule instead of a single numeric value. As being more abstract, the granular format of the preference model offers the required flexibility to increase the level of consistency.

Description

Keywords

Consistency, granularity of information, particle swarm optimization, fuzzy preference relation

Citation

Cabrerizo, F.J., Pedrycz, W., Chiclana, F. and Herrera-Viedma, E. (2014) Improving consistency in fuzzy preference relations with an allocation of information granularity. In: Hamido Fujita, Ali Selamat, Habibollah Haron (Eds.): New Trends in Software Methodologies, Tools and Techniques. Series Frontiers in Artificial Intelligence and Applications, Volume 265.

Rights

Research Institute

Institute of Artificial Intelligence (IAI)