Browsing by Author "Cabrerizo, Francisco Javier"

Now showing 1 - 12 of 12
  • Thumbnail Image
    ItemOpen Access
    Algorithms to Detect and Rectify Multiplicative and Ordinal Inconsistencies of Fuzzy Preference Relations
    (IEEEXplore, 2019-07) Xu, Yejun; Li, Mengqi; Cabrerizo, Francisco Javier; Chiclana, Francisco; Herrera-Viedma, Enrique
    Consistency, multiplicative and ordinal, of fuzzy preference relations (FPRs) is investigated. The geometric consistency index (GCI) approximated thresholds are extended to measure the degree of consistency for an FPR. For inconsistent FPRs, two algorithms are devised (1) to find the multiplicative inconsistent elements, and (2) to detect the ordinal inconsistent elements. An integrated algorithm is proposed to improve simultaneously the ordinal and multiplicative consistencies. Some examples, comparative analysis, and simulation experiments are provided to demonstrate the effectiveness of the proposed methods.
  • Thumbnail Image
    ItemOpen Access
    Consensus in Group Decision Making and Social Networks
    (ICI Publishing House, 2017-09) Herrera-Viedma, Enrique; Cabrerizo, Francisco Javier; Chiclana, Francisco; Wu, Jian; Cobo, Manuel Jesus; Konstantin, Samuylov
    The consensus reaching process is the most important step in a group decision making scenario. This step is most frequently identified as a process consisting of some discussion rounds in which several decision makers, which are involved in the problem, discuss their points of view with the purpose of obtaining the maximum agreement before making the decision. Consensus reaching processes have been well studied and a large number of consensus approaches have been developed. In recent years, the researchers in the field of decision making have shown their interest in social networks since they may be successfully used for modelling communication among decision makers. However, a social network presents some features differentiating it from the classical scenarios in which the consensus reaching processes have been applied. The objective of this study is to investigate the main consensus methods proposed in social networks and bring out the new challenges that should be faced in this research field.
  • Thumbnail Image
    ItemOpen Access
    Editorial - Special issue on intelligent decision support systems based on soft computing and their applications in real-world problems
    (Elsevier, 2018-05-09) Herrera-Viedma, Enrique; Chiclana, Francisco; Dong, Yucheng; Cabrerizo, Francisco Javier
    Editorial of Special issue on intelligent decision support systems based on soft computing and their applications in real-world problems
  • Thumbnail Image
    ItemOpen Access
    Editorial message
    (Springer International Publishing, 2016-12-07) Herrera-Viedma, Enrique; Chiclana, Francisco; Dong, Yucheng; Cabrerizo, Francisco Javier
  • Thumbnail Image
    ItemEmbargo
    A Feedback Mechanism Based on Granular Computing to Improve Consensus in GDM
    (Springer International Publishing, 2017-07-02) Cabrerizo, Francisco Javier; Chiclana, Francisco; Perez, Ignacio Javier; Mata, Francisco; Alons, Sergio; Herrera-Viedma, Enrique
    Group decision making is an important task in real world activities. It consists in obtaining the best solution to a particular problem according to the opinions given by a set of decision makers. In such a situation, an important issue is the level of consensus achieved among the decision makers before making a decision. For this reason, different feedback mechanisms, which help decision makers for reaching the highest degree of consensus possible, have been proposed in the literature. In this contribution, we present a new feedback mechanism based on granular computing to improve consensus in group decision making problems. Granular computing is a framework of designing, processing, and interpretation of information granules, which can be used to obtain a required flexibility to improve the level of consensus within the group of decision makers.
  • Thumbnail Image
    ItemOpen Access
    Group Decision Making: Consensus Approaches Based on Soft Consensus Measures
    (Springer International Publishing, 2017-01-14) Cabrerizo, Francisco Javier; Pérez, Ignacio Javier; Chiclana, Francisco; Herrera-Viedma, Enrique
    A group decision making situation involves multiple decision makers communicating with others to reach a decision. In such a situation, the most important issue is to obtain a decision that is best acceptable by the decision makers, and, therefore, consensus has attained a great attention and it is a major goal of group decision making situations. To measure the closeness among the opinions given by the decision makers, different approaches have been proposed. At the beginning, consensus was meant to be a unanimous and full agreement. However, because this situation is often not reachable in practice, the use of a softer consensus, which assesses the level of agreement in a more flexible way and reflects the large spectrum of possible partial agreements, is a more reasonable approach. Soft consensus approaches better reflects a real human perception of the essence of consensus and, therefore, they have been widely used. The purpose of this contribution is to review the different consensus approaches based on soft consensus measures that have been proposed.
  • Thumbnail Image
    ItemOpen Access
    On Dynamic Consensus Processes in Group Decision Making Problems
    (Elsevier, 2018-05-12) Perez, Ignacio Javier; Cabrerizo, Francisco Javier; Alonso, Sergio; Dong, Yucheng; Chiclana, Francisco; Herrera-Viedma, Enrique
    Consensus in group decision making requires discussion and deliberation between the group members with the aim to reach a decision that reflects the opinions of every group member in order for it to be acceptable by everyone. Traditionally, the consensus reaching problem is theoretically modelled as a multi stage negotiation process, i.e. an iterative process with a number of negotiation rounds, which ends when the consensus level achieved reaches a minimum required threshold value. In real world decision situations, both the consensus process environment and specific parameters of the theoretical model can change during the negotiation period. Consequently, there is a need for developing dynamic consensus process models to represent effectively and realistically the dynamic nature of the group decision making problem. Indeed, over the past few years, static consensus models have given way to new dynamic approaches in order to manage parameter variability or to adapt to environment changes. This paper presents a systematic literature review on the recent evolution of consensus reaching models under dynamic environments and critically analyse their advantages and limitations.
  • Thumbnail Image
    ItemOpen Access
    Revisiting Fuzzy and Linguistic Decision-Making: Scenarios and Challenges for Wiser Decisions in a Better Way
    (IEEE, 2020-12-24) Herrera-Viedma, Enrique; Palomares, Ivan; Li, Cong-Cong; Cabrerizo, Francisco Javier; Dong, Yucheng; Chiclana, Francisco; Herrera, Francisco
    This paper provides a brief tour through the main fuzzy and linguistic decision-making trends, studies, methodologies and models developed in the last 50 years. Fuzzy and linguistic decision-making approaches allow to address complex real-world decision problems where humans exhibit vagueness, imprecision and/or use natural language to assess decision alternatives, criteria, etc. The aim of this paper is threefold. Firstly, the main fuzzy set theory and computing with words based representation paradigms of decision information, with their different levels of expressive richness and complexity, are reviewed. Secondly, three core decision-making frameworks are examined: (1) multi-criteria decision-making, (2) group consensus-driven decision-making, and (3) multi-person multi-criteria decision making. Thirdly, the paper discusses new complex decision making frameworks that have emerged in recent years, where decisions are guided by the “wisdom of the crowd”: their associated challenges are highlighted and considerations on much needed key guidelines for future research in the field are provided.
  • Thumbnail Image
    ItemOpen Access
    Some Trends in Fuzzy Decision Making
    (2022-05) Trillo, José Ramón; Cabrerizo, Francisco Javier; Chiclana, Francisco; Martínez, María Ángeles; Herrera-Viedma, Enrique
    Decision making is a line of research that has been consolidating since its beginnings in the 1960s. The aim of this paper is to show the evolution and future challenges of this line of research, focusing especially on its evaluation and information methods. For this purpose, some issues and trends of the fuzzy decision system are presented. By doing so, it is possible to show which trend fuzzy decision systems will follow and the challenges that may arise.
  • No Thumbnail Available
    ItemMetadata only
    Special issue on Soft Computing based Intelligent Decision Making Systems for Dynamic Frameworks with Real-world Application
    (Elsevier, 2022-06-15) Herrera-Viedma, Enrique; Chiclana, Francisco; Dong, Yucheng; Peng, Yi; Xu, Yejun; Cabrerizo, Francisco Javier
  • Thumbnail Image
    ItemOpen Access
    Strategic Weight Manipulation in Multiple Attribute Decision Making in an Incomplete Information Context
    (IEEE Xplore, 2017-08-24) Liu, Yating; Dong, Yucheng; Chiclana, Francisco; Cabrerizo, Francisco Javier; Herrera-Viedma, Enrique
    In some real-world multiple attribute decision making (MADM) problems, a decision maker can strategically set attribute weights to obtain her/his desired ranking of alternatives, which is called the strategic weight manipulation of the MADM. Sometimes, the attribute weights are given with imprecise or partial information, which is called incomplete information of attribute weights. In this study, we propose the strategic weight manipulation under incomplete information on attributes weights. Then, a series of mixed 0-1 linear programming models (MLPMs) are proposed to derive a strategic weight vector for a desired ranking of an alternative. Finally, a numerical example is used to demonstrate the validity of our models.
  • No Thumbnail Available
    ItemMetadata only
    Theorem Verification of the Quantifier-Guided Dominance Degree with the Mean Operator for Additive Preference Relations
    (MDPI, 2022-06-12) Trillo, Jose Ramon; Cabrerizo, Francisco Javier; Chiclana, Francisco; Martinez, Maria Angeles; Mata, Francisco; Herrera-Viedma, Enrique
    Deciding which film is the best or which portfolio is the best for investment are examples of decisions made by people every day. Decision-making systems aim to help people make such choices. In general, a decision-making system processes and analyses the available information to arrive at the best alternative solution of the problem of interest. In the preference modelling framework, decision-making systems select the best alternative(s) by maximising a score or choice function defined by the decision makers’ expressed preferences on the set of feasible alternatives. Nevertheless, decision-making systems may have logical errors that cannot be appreciated by developers. The main contribution of this paper is the provision of a verification theorem of the score function based on the quantifier-guided dominance degree (QGDD) with the mean operator in the context of additive preference relations. The provided theorem has several benefits because it can be applied to verify that the result obtained is correct and that there are no problems in the programming of the corresponding decision-making systems, thus improving their reliability. Moreover, this theorem acts on different parts of such systems, since not only does the theorem verify that the order of alternatives is correct, but it also verifies that the creation of the global preference relation is correct.