In this article, we introduce the induced ordered weighted geometric (IOWG) operator and its properties. This is a more general type of OWG operator, which is based on the induced ordered weighted averaging (IOWA) operator. We provide some IOWG operators to aggregate multiplicative preference relations in group decision-making (GDM) problems. In particular, we present the importance IOWG (I-IOWG) operator, which induces the ordering of the argument values based on the importance of the information sources; the consistency IOWG (C-IOWG) operator, which induces the ordering of the argument values based on the consistency of the information sources; and the preference IOWG (P-IOWG) operator, which induces the ordering of the argument values based on the relative preference values associated with each one of them. We also provide a procedure to deal with “ties ” regarding the ordering induced by the application of one of these IOWG operators. This procedure consists of a sequential application of the aforementioned IOWG operators. Finally, we analyze the reciprocity and consistency properties of the collective multiplicative preference relations obtained using IOWG operators. © 2004 Wiley Periodicals, Inc. 1.

The ordered weighted geometric (OWG) operator is an aggregation operator that is based on the ordered weighted averaging (OWA) operator and the geometric mean. Its application in multicriteria decision making (MCDM) under multiplicative preference relations has been presented. Some families of OWG operators have been defined. In this article, we present the origin of the OWG operator and we review its relationship to the OWA operator in MCDM models. We show a study of its use in multiplicative decision-making models by providing the conditions under which reciprocity and consistency properties are maintained in the aggregation of multiplicative preference relations performed in the selection process. © 2003 Wiley Periodicals, Inc. 1.

Abstract Internet users are assisted by means of distributed intelligent agents in the information gathering process to find the fittest information to their needs. In this paper we present a distributed intelligent agent model where the communication of the evaluation of the retrieved information among the agents is carried out by using linguistic operators based on the 2-tuple fuzzy linguistic representation as a way to endow the retrieval process with a higher flexibility, uniformity and precision. The 2-tuple fuzzy linguistic representation model allows to make processes of computing with words without loss of information.

The aim of this paper is to propose a procedure to estimate missing preference values when dealing with incomplete fuzzy linguistic preference relations assessed using a two-tuple fuzzy linguistic approach. This procedure attempts to estimate the missing information in an individual incomplete fuzzy linguistic preference relation using only the preference values provided by the respective expert. It is guided by the additive consistency property to maintain experts ’ consistency levels. Additionally, we present a selection process of alternatives in group decision making with incomplete fuzzy linguistic preference relations and analyze the use of our estimation procedure in the decision process. C ○ 2008 Wiley Periodicals, Inc. 1.

This article studies aggregation operators in ordinal scales for their application to clustering (more specifically, to microaggregation for statistical disclosure risk). In particular, we consider these operators in the process of prototype construction. This study analyzes main aggregation operators for ordinal scales [plurality rule, medians, Sugeno integrals (SI), and ordinal weighted means (OWM), among others] and shows the difficulties for their application in this particular setting. Then, we propose two approaches to solve the drawbacks and we study their properties. Special emphasis is given to the study of monotonicity because the operator is proven nonsatisfactory for this property. Exhaustive empirical work shows that in most practical situations, this cannot be considered a problem. 2003 Wiley Periodicals, Inc

In a previous paper, we presented an approach to calculate relational division in fuzzy databases, starting with the GEFRED model. This work centered on dealing with fuzzy attributes and fuzzy values and only the universal quantifier was taken into account since it is the inherent quantifier in classical relational division. In this paper, we present an extension of that division to relax the universal quantifier. With this new system we can use both absolute quantifiers and relative quantifiers irrespective of how the function of the fuzzy quantifier is defined. We also include a comparison with other fuzzy division approaches to relax the universal quantifier that have been published. Furthermore, in this paper we have extended the fuzzy SQL language to express any kind of fuzzy division. � 2001 John Wiley & Sons, Inc. 1.

This paper proposes a generic technique for the evaluation and comparison of the capability of Embedded Systems (ESs) as decision-making aid. The major issue in this area is conducted by comparing and evaluating success factors and the risks associated with each ES. In this regards decisionmaking modelling concepts are based on the identification of capability factors and finding mathematical models to describe or to prescribe best choice. The techniques utilize a combination of subjective and qualitative assumptions and mathematical modelling techniques. The digital cell phone as a sample of ES is analyzed as case study to show the application of the proposed approach. The results show the high performance of this methodology for capability evaluation of such systems.

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