Examinando por Autor "Martínez, Luis"
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Ítem A Cohesion-driven Consensus Reaching Process for Large Scale Group Decision Making under a Hesitant Fuzzy Linguistic Term Sets Environment(Elsevier, 2021-05) Rodríguez, Rosa M.; Labella, Álvaro; Sesma-Sara, Mikel; Bustince, Humberto; Martínez, LuisLarge-scale group decision-making (LSGDM) under uncertainty modelled by comparative linguistic expressions based on a hesitant fuzzy linguistic term set (HFLTS) has recently attracted the interest of many researchers and research, due to the necessity of its function in LSGDM, and the challenges it faces such as the managing of the scalability problem, uncertainty of experts’ opinions and dealing with polarized conflicting opinions. To smooth out such discrepancies and obtain agreed solutions Consensus Reaching Processes (CRPs) for LSGDM have been applied, in which experts are grouped into sub-groups according to the closeness of their opinions to deal with scalability. However, most CRPs for LSGDM are driven by a majority rule, in which larger sub-groups, where there might be internal disagreements, lead the consensus. In such processes, the internal disagreements can produce unsatisfactory solutions. Consequently, the majority view should be complemented by additional mechanisms that also measure the strength of the sub-groups’ opinions. A good measurement of such strength is the cohesion among the sub-group members. Therefore, in this paper, a new cohesion measure for HFLTS based on restricted equivalence functions for measuring the experts’ sub-group cohesiveness is introduced to drive the consensus process together the majority and thus reduce the impact of internal disagreements risen in majority driven CRPs. It is then integrated in a new cohesion-driven CRP approach based on LSGDM to deal with comparative linguistic expressions based on HFLTS. An experimental analysis on different large scale scenarios will show the performance and importance of cohesion in consensus based LSGDM.Ítem A comprehensive minimum cost consensus model for large scale group decision making for circular economy measurement(ELSEVIER, 2022-02) Rodríguez, Rosa M.; Labella, Álvaro; Núñez-Cacho, Pedro; Molina-Moreno, Vicente; Martínez, LuisSince the first report on the Circular Economy (CE) appeared in 2013, there has been an explosion of interest in the subject by society and the business world. Thus, a base of academic literature has been developed, seeking the establishment of principles that serve as a theoretical foundation for the concept of CE. Governments demand to know how organizations are evolving in the transition towards the new production model. However, despite the efforts of researchers and companies to develop effective measurement systems, it is not easy to decide which aspects to measure, nor to determine the degree of intensity in which an organization implements the CE model. The measurement proposals combine different methodologies that are costly and time consuming procedures. We propose a comprehensive minimum cost consensus model for large scale group decision making, in which the initial experts’ preferences are automatically adjusted to obtain the measurement and cost of indicators, so that they might agree on the measurements implemented. The main aim of this research is not only to provide a quick, useful and correct method for measuring the CE, but also to show its correctness, advantages and usefulness by comparing its performance with a real case.Ítem A Consensus-Driven Group Recommender System(Wiley Periodicals, Inc, 2015) Castro, Jorge; Quesada, Francisco J.; Palomares, Iván; Martínez, LuisRecommender systems aim at filtering large amounts of information for users, providing them with those pieces of information which better meet their preferences or needs. Such systems have been traditionally used in diverse areas, such as e-commerce or tourism. Within this context, group recommender systems address the problem of generating recommendations for groups of users who might have different interests. Although different aggregation processes have been extensively utilized in real-life applications to generate group recommendations, such processes do not guarantee that the list of products recommended to the group reflect a high agreement level among its members' individual preferences. Given the need for considering the added value of obtaining group recommendations under a high agreement level, this paper presents a novel group recommender system methodology that attempts to reach a high level of consensus among individual recommendations of group members. To do this, and inspired by existing group decision-making approaches in the literature, a consensus reaching process is carried out to bring such individual recommendations closer to each other before delivering the group recommendations.Ítem A cost consensus metric for Consensus Reaching Processes based on a comprehensive minimum cost model(Elsevier, 2020-03) Labella, Álvaro; Liu, Hongbin; Rodríguez, Rosa M.; Martínez, LuisConsensus Reaching Processes (CRPs) have recently acquired much more importance within Group Decision Making real-world problems because of the demand of either agreed or consensual solutions in such decision problems. Hence, many CRP models have been proposed in the specialized literature, but so far there is not any clear objective to evaluate their performance in order to choose the best CRP model. Therefore, this research aims at developing an objective metric based on the cost of modifying experts’ opinions to evaluate CRPs in GDM problems. First, a new and comprehensive minimum cost consensus model that considers distance to global opinion and consensus degree is presented. This model obtains an optimal agreed solution with minimum cost but this solution is not dependent on experts’ opinion evolution. Therefore, this optimal solution will be used to evaluate CRPs in which experts’ opinion evolution is considered to achieve an agreed solution for the GDM. Eventually, a comparative performance analysis of different CRPs on a GDM problem will be provided to show the utility and validity of this cost metric.Ítem A Group Decision Making Model Dealing with Comparative Linguistic Expressions based on Hesitant Fuzzy Linguistic Term Sets(Elsevier, 2013-08) Rodríguez, Rosa M.; Martínez, Luis; Herrera, FranciscoThe complexity and impact of many real world decision making problems lead to the necessity of considering multiple points of view, building group decision making problems in which a group of experts provide their preferences to achieve a solution. In such complex problems uncertainty is often present and although the use of linguistic information has provided successful results in managing it, these are sometimes limited because the linguistic models use single-valued and predefined terms that restrict the richness of freely eliciting the preferences of the experts. Usually, experts may doubt between different linguistic terms and require richer expressions to express their knowledge more accurately. However, linguistic group decision making approaches do not provide any model to make more flexible the elicitation of linguistic preferences in such hesitant situations. In this paper is proposed a new linguistic group decision model that facilitates the elicitation of flexible and rich linguistic expressions, in particular through the use of comparative linguistic expressions, close to human beings’ cognitive models for expressing linguistic preferences based on hesitant fuzzy linguistic term sets and context-free grammars. This model defines the group decision process and the necessary operators and tools to manage such linguistic expressions.Ítem A large scale consensus reaching process managing group hesitation(Elsevier, 2018-11) Rodríguez, Rosa M.; Labella, Álvaro; De Tré, Guy; Martínez, LuisNowadays due to the social networks and the technological development, large-scale group decision making (LSGDM) problems are fairly common and decisions that may affect to lots of people or even the society are better accepted and more appreciated if they agreed. For this reason, consensus reaching processes (CRPs) have attracted researchers attention. Although, CRPs have been usually applied to GDM problems with a few experts, they are even more important for LS-GDM, because differences among a big number of experts are higher and achieving agreed solutions is much more complex. Therefore, it is necessary to face some challenges in LS-GDM. This paper presents a new adaptive CRP model to deal with LS-GDM which includes: (i) a clustering process to weight experts’ sub-groups taking into account their size and cohesion, (ii) it uses hesitant fuzzy sets to fuse expert’s sub-group preferences to keep as much information as possible and (iii) it defines an adaptive feedback process that generates advice depending on the consensus level achieved to reduce the time and supervision costs of the CRP. Additionally, the proposed model is implemented and integrated in an intelligent CRP support system, so-called AFRYCA 2.0 to carry out this new CRP on a case study and compare it with existing models.Ítem A Linguistic Group Best–Worst Method for Measuring Good Governance in the Third Sector: A Spanish Case Study(Springer, 2022-03-23) Licerán-Gutiérrez, Ana; Ortega-Rodríguez, Cristina; Moreno-Albarracín, Antonio Luis; Labella, Álvaro; Rodríguez, Rosa María; Martínez, LuisThe need of Non-profit Organizations (NPOs) of generating trust and credibility, to their stakeholders by an efficient management of their resources, lead them to openly show that they develop adequate good governance practices. But this is not a simple task and few research has been done on measuring methods of good governance in this field; without achieving an agreement about the best procedure. This paper aims at facilitating the measurement of good governance practices in NPOs by a fuzzy linguistic consensus-based group multi-criteria decision-making (MCGDM) model that will provide agreed and easy-understanding weights for a list of indicators proposed by the stakeholders and entities in such good governance practices. To do that, a linguistic 2-tuple BWM method with a consensus reaching process (CRP) will be developed and then applied to a real-world case in Spain, in which a group of experts from significant Spanish NPOs will assess the list of indicators proposed by the most representative entities (the alliance between the non-governmental organizations (NGO) Platform for Social Action, and the NGO Coordinator for Development (CONGDE) to obtain a prioritization of such indicators for measuring the good governance practices in Spanish NPOs.Ítem A Linguistic Metric for Consensus Reaching Processes Based on ELICIT Comprehensive Minimum Cost Consensus Models(IEEE, 2023-05) García-Zamora, Diego; Labella, Álvaro; Rodríguez, Rosa M.; Martínez, LuisLinguistic group decision making (LiGDM) aims at solving decision situations involving human decision makers (DMs) whose opinions are modeled by using linguistic information. To achieve agreed solutions that increase DMs' satisfaction toward the collective solution, linguistic consensus reaching processes (LiCRPs) have been developed. These LiCRPs aim at suggesting DMs to change their original opinions to increase the group consensus degree, computed by a certain consensus measure. In recent years, these LiCRPs have been a prolific research line, and consequently, numerous proposals have been introduced in the specialized literature. However, we have pointed out the nonexistence of objective metrics to compare these models and decide which one presents the best performance for each LiGDM problem. Therefore, this article aims at introducing a metric to evaluate the performance of LiCRPs that takes into account the resulting consensus degree and the cost of modifying DMs' initial opinions. Such a metric is based on a linguistic comprehensive minimum cost consensus (CMCC) model based on Extended Comparative Linguistic Expressions with Symbolic Translation information that models DMs' hesitancy and provides accurate Computing with Words processes. In addition, the linguistic CMCC optimization model is linearized to speed up the computational model and improve its accuracy.Ítem A Linguistic Metric for Consensus Reaching Processes Based on ELICIT Comprehensive Minimum Cost Consensus Models(IEEE, 2023) García-Zamora, Diego; Labella, Álvaro; Rodríguez, Rosa M.; Martínez, LuisLinguistic group decision making (LiGDM) aims at solving decision situations involving human decision makers (DMs) whose opinions are modeled by using linguistic information. To achieve agreed solutions that increase DMs' satisfaction toward the collective solution, linguistic consensus reaching processes (LiCRPs) have been developed. These LiCRPs aim at suggesting DMs to change their original opinions to increase the group consensus degree, computed by a certain consensus measure. In recent years, these LiCRPs have been a prolific research line, and consequently, numerous proposals have been introduced in the specialized literature. However, we have pointed out the nonexistence of objective metrics to compare these models and decide which one presents the best performance for each LiGDM problem. Therefore, this article aims at introducing a metric to evaluate the performance of LiCRPs that takes into account the resulting consensus degree and the cost of modifying DMs' initial opinions. Such a metric is based on a linguistic comprehensive minimum cost consensus (CMCC) model based on Extended Comparative Linguistic Expressions with Symbolic Translation information that models DMs' hesitancy and provides accurate Computing with Words processes. In addition, the linguistic CMCC optimization model is linearized to speed up the computational model and improve its accuracy.Ítem An Analysis of Symbolic Linguistic Computing Models in Decision Making(Taylor and Francis, 2012-07) Rodríguez, Rosa M.; Martínez, LuisIt is common that experts involved in complex real-world decision problems use natural language for expressing their knowledge in uncertain frameworks. The language is inherent vague, hence probabilistic decision models are not very suitable in such cases. Therefore, other tools such as fuzzy logic and fuzzy linguistic approaches have been successfully used to model and manage such vagueness. The use of linguistic information implies to operate with such a type of information, i.e. processes of computing with words (CWW). Different schemes have been proposed to deal with those processes, and diverse symbolic linguistic computing models have been introduced to accomplish the linguistic computations. In this paper, we overview the relationship between decision making and CWW, and focus on symbolic linguistic computing models that have been widely used in linguistic decision making to analyse if all of them can be considered inside of the CWW paradigm.Ítem An optimal Best-Worst prioritization method under a 2-tuple linguistic environment in decision making(ELSEVIER, 2021-05) Labella, Álvaro; Dutta, Bapi; Martínez, LuisMulti-criteria group decision making (MCGDM) deals with decision makers who evaluate alternatives over several criteria. MCGDM problems evolve in tandem with the progress of our society. Such progress has given rise to the large-scale group decision making (LS-GDM) problems in which hundreds of decision makers may participate in the decision process and new challenges to face such as groups’ formation and polarization opinions. Most real world MCGDM problems present changing contexts with uncertainty that cannot be modeled by numerical values. Under these circumstances, the use of linguistic variables and computing with words (CW) processes have provided successfully results. Concretely, the 2-tuple linguistic computational model stands out because its precise linguistic computations and high interpretability. On the other hand, pairwise comparison is a widely used elicitation technique in MCGDM, but a large number of comparisons might lead inconsistent decision makers’ preferences. The Best-Worst method (BWM) reduces the number of pairwise comparisons and the inconsistency in decision makers’ opinions. Several BWM approaches have been proposed to manage linguistic information but none of them take advantage of the 2-tuple linguistic computational process based on the CW approach, which would allow to obtain precise and understandable results. This paper aims to present an extended 2-tuple BWM to reduce the number of pairwise comparisons in MCGDM problems and model the uncertainty associated with them to accomplish accuracy computations and obtaining interpretable results. Moreover, we apply our proposal to LS-GDM scenarios in which polarization opinions and sub-groups identification, ignored from any of BWM proposals, are considered. Finally, the new model is applied to several illustrative MCGDM problems.Ítem Analyzing the performance of classical consensus models in large scale group decision making: A comparative study(ELSEVIER, 2018-06) Labella, Álvaro; Liu, Yaya; Rodríguez, Rosa M.; Martínez, LuisConsensus reaching processes (CRPs) in group decision making (GDM) attempt to reach a mutual agreement among a group of decision makers before making a common decision. Different consensus models have been proposed by different authors in the literature to facilitate CRPs. Classical CRP models focus on achieving an agreement on GDM problems in which few decision makers participate. However, nowadays, societal and technological trends that demand the management of larger scale of decision makers add new requirements to the solution of consensus-based GDM problems. This paper presents a comparative study of different classical CRPs applied to large-scale GDM in order to analyze their performance and find out which are the main challenges that these processes face in large-scale GDM. Such analyses will be developed in a java-based framework (AFRYCA 2.0) simulating different scenarios in large scale GDM.Ítem Comprehensive minimum cost models for large scale group decision making with consistent fuzzy preference relations(Elsevier, 2021-03) Rodríguez, Rosa M.; Labella, Álvaro; Dutta, Bapi; Martínez, LuisNowadays, society demands group decision making (GDM) problems that require the participation of a large number of experts, so-called large scale group decision making (LS-GDM) problems. Logically, the more experts are involved in the decision making process, the more common is the emergence of disagreements in the group. For this reason, consensus reaching processes (CRPs) are key in the resolution of these problems in order to smooth such disagreements in the group and reach consensual solutions. A CRP requires that experts are receptive to change their initial preferences, but demanding excessive changes could lead to deadlocks. The well-known minimum cost consensus (MCC) model allows to obtain an agreed solution by preserving experts’ preferences as much as possible. However, this MCC model only considers the distance among experts and collective opinion, which is not enough to guarantee a desired degree of consensus. To overcome this limitation, it was proposed comprehensive MCC models (CMCC) in which both consensus degree and distance are considered, and CMCC models deal with fuzzy preference relations (FPRs) for modeling experts’ opinions. However, these models are not efficient to deal with LS-GDM problems and the FPRs consistency is ignored in them. Therefore, this paper aims to propose new CMCC models focused on LS-GDM problems in which experts use FPRs whose consistency is taken into account in order to obtain reliable results. A case study is introduced to show the effectiveness of the proposed models.Ítem Consensual Group-AHPSort: Applying consensus to GAHPSort in sustainable development and industrial engineering(ELSEVIER, 2021-02) Labella, Álvaro; Ishizaka, Alessio; Martínez, LuisMulti-Criteria Group Decision Making (MCGDM) deals with the process of taking decisions among a number of decision makers who evaluate different alternatives on several criteria that may be conflicting. In such a type of problems conflicts may are not only related to the criteria but also with the decision makers that could result in unsatisfactory solutions because of disagreements or deadlocks to achieve a decision. To avoid these undesirable results, consensus processes have been applied to group decision. The application of MCGDM has been mainly focused on decision problems for ranking and choice alternatives but, similarly to multi-criteria decision making, other types of problems such as sorting and description can be formulated. Although, a few number of MCGDM-sorting models, comparing with ranking and choice ones, have been proposed their importance and impact is quite significant nowadays. Hence, our aim is to consider the recent proposal on Group-AHPSort that did not consider any disagreement measure across the sorting decision process and study how the use of consensus processes can avoid some misclassifications or disagreements among the group of decision makers taking part in the MCGDM problem. To illustrate our approach, a case study focusing on the sorting of five European Union countries according to their sustainable development performance regarding social issues will show the importance and utility of detecting and smoothing disagreements in Group-AHPSort.Ítem Consistency of hesitant fuzzy linguistic preference relations: An interval consistency index(Elsevier, 2018-03) Li, CongCong; Rodriguez, Rosa M.; Herrera, Francisco; Martínez, Luis; Dong, YuchengThe study of hesitant consistency is very important in decision-making with hesitant fuzzy linguistic preference relations (HFLPRs), and generally the normalization method is used as a tool to measure the consistency degree of a HFLPR. In this paper we propose a new hes- itant consistency measure, called interval consistency index, to estimate the consistency range of a HFLPR. The underlying idea of the interval consistency index consists of measur- ing the worst consistency index and the best consistency index of a HFLPR. Furthermore, by comparative study, a connection is shown between the interval consistency index and the normalization method, demonstrating that the normalization method should be con- sidered as an approximate average consistency index of a HFLPR.Ítem Hesitant Fuzzy Sets: State of the Art and Future Directions(Wiley, 2014-04) Rodríguez, Rosa M.; Martínez, Luis; Torra, Vicenç; Xu, Zeshui; Herrera, FranciscoThe necessity of dealing with uncertainty in real world problems has been a long-term research challenge that has originated different methodologies and theories. Fuzzy sets along with their extensions, such as type-2 fuzzy sets, interval-valued fuzzy sets, and Atanassov’s intuitionistic fuzzy sets, have provided a wide range of tools that are able to deal with uncertainty in different types of problems. Recently, a new extension of fuzzy sets so-called hesitant fuzzy sets has been introduced to deal with hesitant situations, which were not well managed by the previous tools. Hesitant fuzzy sets have attracted very quickly the attention of many researchers that have proposed diverse extensions, several types of operators to compute with such types of information, and eventually some applications have been developed. Because of such a growth, this paper presents an overview on hesitant fuzzy sets with the aim of providing a clear perspective on the different concepts, tools and trends related to this extension of fuzzy sets.Ítem Managing experts behavior in large-scale consensus reaching processes with uninorm aggregation operators(Elsevier, 2015-10) Quesada, Francisco J.; Palomares, Iván; Martínez, LuisIn many real-life large scale group decision making problems, it can be necessary and convenient a consensus reaching process, which is an iterative procedure aimed at seeking a high degree of agreement amongst experts’ preferences before making a group decision. Although a wide variety of models and approaches have been proposed and developed to support consensus reaching processes, in large groups there are some important aspects that still require further study, such as the treatment of experts’ behaviors that could hamper reaching the wanted agreement. More specifically, it would be necessary an approach to deal with experts properly, based on the overall behavior they present during the discussion process, as well as reinforcing repeated patterns of cooperative (or uncooperative) behavior adopted by experts. This paper presents an expert weighting methodology for consensus reaching processes in large-scale group decision making, that incorporates the use of uninorm aggregation operators. Such operators, which are characterized by their property of full reinforcement, are used in the proposed methodology to allow the experts’ weighting based on their overall behavior during the consensus process and the behavior evolution across the time. This proposal is integrated in a consensus model for large-scale group decision making problems under uncertainty, and it is put in practice to show an illustrative example of its effectiveness and improvements with respect to other approaches.Ítem Optimization algorithm for learning consistent belief rule-base from examples(Springer Link, 2011-10) Liu, Jun; Martínez, Luis; Ruan, Da; Rodríguez, Rosa M.; Calzada, AlbertoA belief rule-based inference approach and its corresponding optimization algorithm deal with a rule-base with a belief structure called a belief rule base (BRB) that forms a basis in the inference mechanism. In this paper, a new learning method is proposed based on the given sample data for optimally generating a consistent BRB. The focus is given on the consistency of BRB knowing that the consistency conditions are often violated if the system is generated from real world data. The measurement of BRB inconsistency is incorporated in the objective function of the optimization algorithm. This process is formulated as a non-linear constraint optimization problem and solved using the optimization tool provided in MATLAB. A numerical example is demonstrated the effectiveness of the proposed algorithm.Ítem Phonendo: a platform for publishing wearable data on distributed ledger technologies(Springer, 2023-08-07) Moya, Francisco; Quesada, Francisco J.; Martínez, Luis; Estrella, Fco JavierNowadays, Internet of Things (IoT) devices, especially wearable devices, are commonly integrated into modern intelligent healthcare software. These devices enable medical practitioners to monitor pervasively patients’ parameters outside the clinical environment. However, the ease of manipulating wearable devices and their data streams raises concerns regarding patient privacy and data trust. Distributed ledger technologies (DLT) offer solutions to enhance resistance against information manipulation and eliminate single points of failure. By leaveraging DLT, wearable-based solutions can be developed with a wider range of capabilities. This paper carries out an analysis of shortcomings, limitations, potential applications and needs in the medical domain, to introduce Phonendo 1.0, a DLT–IoT-based platform designed to capture data streams from wearable devices and publishing them on a distributed ledger technology infrastructure. The architecture and its difference services are justified based on the identified needs and challenges in the medical domain.Ítem Transparency indicators to improve accountability for non-profit organizations: A Spanish case study(Vilnius Tech Journals, 2021-05-04) Moreno-Albarracín, Antonio Luis; Ortega-Rodríguez, Cristina; Licerán-Gutiérrez, Ana; Labella, Álvaro; Martínez, LuisWe are currently witnessing the development of a set of organizations that have been entrusted with meeting the very diverse needs of citizens. As a result, they receive funds, in order to ensure they are managed appropriately. The transparency of the information revealed by Non-profit Organizations (NPOs) has become of increasing interest to public authorities and research. However, very few studies empirically measure the extent of transparency in NPOs. Only a handful checked the compliance of various indicators, lacking agreement on which ones to include and their weighting. To address this issue, this study empirically validates the weighting of the indicators from the alliance between the Platform for Social Action NGO and the Spanish Coordinator for Development NGO (CONGDE) document with experts in NPOs’ opinions. We use the Best-Worst Method (BWM) to optimally assign weights to multi-criteria decision making situations. Our results show interesting differences in the level of importance given to the indicators by public authorities and experts, suggesting the need for a revision of the importance proposed.