Visualization and evolution of the scientific structure of fuzzy sets research in Spain

Introduction. Presents the first bibliometric study on the evolution of the fuzzy sets theory field. It is specially focused on the research carried out by the Spanish comunity. Method. The CoPalRed software, for network analysis, and the co-word analysis technique are used. Analysis. Bibliometric maps showing the main associations among the main concepts in the field are provided for the periods 1965-1993, 1994-1998, 1999-2003 and 2004-2008. Results. The bibliometric maps obtained provide insight into the structure of the fuzzy sets theory research in the Spanish community, visualize the research subfields, and show the existing relationships between those subfields. Furthermore, we compare the Spanish community with other countries (the USA and Canada; the UK and Germany; and Japan and Peoples Republic of China). Conclusions. As a result of the analysis, a complete study of the evolution of the Spanish fuzzy sets community and an analysis of its international importance are presented.Introducción. Presenta el primer estudio bibliométrico sobre la evolución del campo de la teoría de conjuntos difusos. Se centra especialmente en la investigación llevada a cabo por la comunidad española. Método. Se utiliza el software de CoPalRed, para el análisis de red, y la técnica de anñlisis de co-palabras. Aná;lisis. Se proporcionan mapas bibliométricos mostrando las principales asociaciones entre los principales conceptos en el campo para los períodos de 1965-1993, 1994-1998, 1999-2003 y 2004-2008. Resultados. Los mapas bibliométricos obtenidos proporcionan conocimientos sobre la estructura de la investigación sobre teoría de conjuntos difusos en la comunidad española, visualizan los subcampos de investigación y muestran las relaciones existentes entre los subcampos. Ademñs, se compara la comunidad española con otros países (Estados Unidos y Canada; Reino Unido y Alemania; y Japón y República Popular China). Conclusiones. Como resultado de los análisis, se presenta un estudio completo de la evolución de la comunidad española en conjuntos difusos y un anñlisis de su importancia internacional.This work has been supported by the Spanish project FUZZY-LING, Cod. TIN2007-61079, granted by the Spanish Agency for Education and Science (Ministerio de Educación y Ciencia)

A Variance-Based Consensus Degree in Group Decision Making Problems

The variance is a well-known statistical measure and is frequently used for the calculation of variability. This concept can be used to obtain the degree of agreement in groups that have to make decisions. In this study, we propose the use of a variance derivative as an alternative for the calculation of the degree of consensus for Group Decision Making problems with fuzzy preference relations. As revealed by a subsequent comparative study, the values obtained by this new method are comparable to the values obtained by means of frequently used methods that employ distance functions and aggregation operators, while it turns out to be a simpler application method

Group consensus measurement in MADM with multiple preference formats

An approach is proposed for measuring the group consensus in multiple attribute decision-making (MADM) problems with experts’ various preference information on alternatives. In the approach, multiple decision-makers give their preference information on alternatives in different formats. The uniformities and aggregation process with fuzzy majority method are employed to obtain the social fuzzy preference relation on the alternatives. Accordingly, the ranking values of the alternatives are obtained based on the obtained individual expert’s fuzzy preference relation, and the social one. The group consensus can be measured based on the ranking values of the alternatives that are derived from the individual expert’s preference information and the social one. An example of selecting robots is presented as an illustration

Using GIS and Multi-criteria Decision Analysis for Conflict Resolution in Land Use Planning

AbstractBased on the principles of sustainable development, land use planning often requires the compromise between economic development and environmental conservation while advocating social justice. Given that ideas, values, and attitudes vary among the stakeholders involved, land use planning inevitably incurs a variety of conflicts. The conflicts in land use planning can be described from the perspective of the conflicts among land use types and the conflicts among stakeholders. Accordingly, land use planning can be conceived as the process of dealing with conflicts among different land use types through resolving the conflicts among stakeholders. This study centers around two important issues in land use planning: land use allocation and specific land use proposal deliberation. A Conflict Resolution Framework was proposed based on GIS and Multi-criteria Decision Analysis techniques. A Consensus Building Model was established to address the conflicts among different stakeholders with competing interests in the process of land use allocation. A Spatial Conflict Resolution Strategy was developed to help stakeholders and planners formulate specific land use proposals through an iterative modification process. The both models were tested and evaluated in the context of Lantau, Island Hong Kong. Moreover, the challenges of this research and future work are also covered in this paper

A variance-based consensus degree in group decision making problems

The variance is a well-known statistical measure and is frequently used for the calculation of variability. This concept can be used to obtain the degree of agreement in groups that have to make decisions. In this study, we propose the use of a variance derivative as an alternative for the calculation of the degree of consensus for Group Decision Making problems with fuzzy preference relations. As revealed by a subsequent comparative study, the values obtained by this new method are comparable to the values obtained by means of frequently used methods that employ distance functions and aggregation operators, while it turns out to be a simpler application method

REVIEW OF MODELING PREFERENCES FOR DECISION MODELS

A group decision problem is set in environments where there is a common issue to solve, a set of possible options to choose, and a set of individuals who are experts and express their opinions about the set of possible alternatives with the intention to reach a collective decision as the unique solution of the problem in question. The modeling of the preferences of the decision-maker is an essential stage in the construction of models used in the theory of decision, operations research, economics, etc. On decision problems experts use models of representation of preferences that are close to their disciplines or fields of work. The structures of information most commonly used for the representation of the preferences of experts are vectors of utility, orders of preference and preference relations. In decision problems, the expression of preferences domain is the domain of information used by the experts to express their preferences, the main are numerical, linguistic, and intervalar stressing the multi-granular linguistic. This paper is a review of these concepts. Its purpose is to provide a guide of bibliographic references for these concepts, which are briefly discussed in this document

The dynamics of consensus in group decision making: investigating the pairwise interactions between fuzzy preferences.

In this paper we present an overview of the soft consensus model in group decision making and we investigate the dynamical patterns generated by the fundamental pairwise preference interactions on which the model is based. The dynamical mechanism of the soft consensus model is driven by the minimization of a cost function combining a collective measure of dissensus with an individual mechanism of opinion changing aversion. The dissensus measure plays a key role in the model and induces a network of pairwise interactions between the individual preferences. The structure of fuzzy relations is present at both the individual and the collective levels of description of the soft consensus model: pairwise preference intensities between alternatives at the individual level, and pairwise interaction coefficients between decision makers at the collective level. The collective measure of dissensus is based on non linear scaling functions of the linguistic quantifier type and expresses the degree to which most of the decision makers disagree with respect to their preferences regarding the most relevant alternatives. The graded notion of consensus underlying the dissensus measure is central to the dynamical unfolding of the model. The original formulation of the soft consensus model in terms of standard numerical preferences has been recently extended in order to allow decision makers to express their preferences by means of triangular fuzzy numbers. An appropriate notion of distance between triangular fuzzy numbers has been chosen for the construction of the collective dissensus measure. In the extended formulation of the soft consensus model the extra degrees of freedom associated with the triangular fuzzy preferences, combined with non linear nature of the pairwise preference interactions, generate various interesting and suggestive dynamical patterns. In the present paper we investigate these dynamical patterns which are illustrated by means of a number of computer simulations.

Distance-based consensus models for fuzzy and multiplicative 3 preference relations

This paper proposes a distance-based consensus model for fuzzy preference relations where the weights of fuzzy preference relations are automatically determined. Two indices, an individual to group consensus index (ICI) and a group consensus index (GCI), are introduced. An iterative consensus reaching algorithm is presented and the process terminates until both the ICI and GCI are controlled within predefined thresholds. The model and algorithm are then extended to handle multiplicative preference relations. Finally, two examples are illustrated and comparative analyses demonstrate the effectiveness of the proposed methods