Premium
Induced cluster‐based OWA operators with reliability measures and the application in group decision‐making
Author(s) -
Yi Pingtao,
Li Weiwei
Publication year - 2019
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.22063
Subject(s) - operator (biology) , weighting , cluster (spacecraft) , reliability (semiconductor) , mathematics , variable (mathematics) , group decision making , order (exchange) , computer science , preference , data mining , statistics , psychology , repressor , mathematical analysis , social psychology , biochemistry , power (physics) , quantum mechanics , transcription factor , radiology , programming language , medicine , physics , finance , economics , gene , chemistry
Considering the distributed structural characteristics of arguments to be aggregated, we propose a new type of aggregation operator, called induced cluster‐based ordered weighted averaging (OWA; abbreviated as cluster‐IOWA) operator, in this article. The main characteristic of the cluster‐IOWA operator is that the arguments are aggregated by local clusters, and the order‐inducing variable is used for representing a particular characteristic with respect to a local cluster. The cluster‐OWA operator is commutativity, idempotence, and boundedness. We then discuss two important issues with respect to the cluster‐IOWA operator. The order‐inducing variables are determined by considering the overall reliability of the local cluster. Based on this, the position weighting vector of the local clusters is designed by taking into account both the reliability measures and the decision maker's preference. Finally, a numerical example, regarding the performance evaluation of middle managers carried out by a group of participants, is developed to illustrate the application and validity of the cluster‐IOWA operator.