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Professor Enrique Herrera-Viedma

Job: Professor of Soft Computing and Intelligent Information Systems

Faculty: Computing, Engineering and Media

School/department: School of Computer Science and Informatics

Address: De Montfort University, The Gateway, Leicester, LE1 9BH

T: N/A

E: enrique.herrera-viedma@dmu.ac.uk

W: www.dmu.ac.uk/

 

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Research group affiliations

  1. DIGITS – De Montfort University Interdisciplinary Group in Intelligent Transport Systems
  2. Centre for Computational Intelligence

Publications and outputs

  • Social network group decision making: Characterization, taxonomy, challenges and future directions from an AI and LLMs perspective
    dc.title: Social network group decision making: Characterization, taxonomy, challenges and future directions from an AI and LLMs perspective dc.contributor.author: Cao, Mingshuo; Gai, Tiantian; Wu, Jian; Chiclana, Francisco; Zhang, Zhen; Dong, Yucheng; Herrera-Viedma, Enrique; Herrera, Francisco dc.description.abstract: In the past decade, social network group decision making (SNGDM) has experienced significant advancements. This breakthrough is largely attributed to the rise of social networks, which provides crucial data support for SNGDM. As a result, it has emerged as a rapidly developing research field within decision sciences, attracting extensive attention and research over the past ten years. SNGDM events involve complex decision making processes with multiple interconnected stakeholders, where the evaluation of alternatives is influenced by network relationships. Since this research has evolved from group decision making (GDM) scenarios, there is currently no clear definition for SNGDM problems. This article aims to address this gap by first providing a clear definition of the SNGDM framework. It describes basic procedures, advantages, and challenges, serving as a foundational portrait of the SNGDM framework. Furthermore, this article offers a macro description of the literature on SNGDM over the past decade based on bibliometric analysis. Solving SNGDM problems effectively is challenging and requires careful consideration of the impact of social networks among decision-makers and the facilitation of consensus between different participants. Therefore, we propose a classification and overview of key elements for SNGDM models based on the existing literature: trust models, internal structure, and consensus mechanism for SNGDM. This article identifies the research challenges in SNGDM and points out the future research directions from two dimensions: first, the key SNGDM methodologies and second, the opportunities from artificial intelligence technology, in particular, combining large language models and multimodal fusion technologies. This look will be analyzed from a double perspective, both from the decision problem and from the technology views. dc.description: The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
  • A Trust Incentive Driven Feedback Mechanism With Risk Attitude for Group Consensus in Social Networks
    dc.title: A Trust Incentive Driven Feedback Mechanism With Risk Attitude for Group Consensus in Social Networks dc.contributor.author: Ji, Feixia; Wu, Jian; Chiclana, Francisco; Sun, Qi; Herrera-Viedma, Enrique dc.description.abstract: Trust relationships can facilitate cooperation in collective decisions. Using behavioral incentives via trust to encourage voluntary preference adjustments improves consensus through mutual agreement. This article aims to establish a trust incentive-driven framework for enabling consensus in social network group decision making (SN-GDM). First, a trust incentive mechanism is modeled via interactive trust functions that integrate risk attitude. The inclusion of risk attitude is crucial as it reflects the diverse ways decision makers (DMs) respond to uncertainty in trusting others’ judgments, capturing the varied behaviors of risky, neutral, and insurance DMs in the consensus process. Inconsistent DMs then adjust opinions in exchange for heightened trust. This mechanism enhances the importance degrees via a new weight assignment method, serving as a reward to motivate DMs to further align with the majority. Subsequently, a trust incentive-driven bounded maximum consensus model is proposed to optimize cooperation dynamics while preventing over-compensation of adjustments. Simulations and comparative analysis demonstrate the model’s efficacy in facilitating cooperation through tailored trust incentive mechanisms that account for these diverse risk preferences. Finally, the approach is applied to evaluate candidates for the Norden Shipping Scholarship, providing a cooperation-focused SN-GDM framework for achieving mutually agreeable solutions while acknowledging the impact of individual risk attitude on trust-based interactions. dc.description: The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
  • Supporting group cruise decisions with online collective wisdom: An integrated approach combining review helpfulness analysis and consensus in social networks
    dc.title: Supporting group cruise decisions with online collective wisdom: An integrated approach combining review helpfulness analysis and consensus in social networks dc.contributor.author: Ji, Feixia; Wu, Jian; Chiclana, Francisco; Sun, Qi; Liang, Changyong; Herrera-Viedma, Enrique dc.description.abstract: Online cruise reviews provide valuable insights for group cruise evaluations, but the vast quantity and varied quality of reviews pose significant challenges. Further complications arise from the intricate social network structures and divergent preferences among decision-makers (DMs), impeding consensus on cruise evaluations. This paper proposes a novel two-stage methodology to address these issues. In the first stage, an inherent helpfulness level–personalized helpfulness level (IHL–PHL) model is devised to evaluate review helpfulness, considering not only inherent review quality but also personalized relevance to the specific DMs’ contexts. Leveraging deep learning techniques like Sentence-BERT and neural networks, the IHL–PHL model identifies high-quality, highly relevant reviews tailored as decision support data for DMs with limited cruise familiarity. The second stage facilitates consensus among DMs within overlapping social trust networks. A binary trust propagation method is developed to optimize trust propagation across overlapping communities by strategically selecting key bridging nodes. Building upon this, a constrained maximum consensus model is proposed to maximize group agreement while limiting preference adjustments based on trust-constrained willingness, thereby preventing inefficient iterations. The proposed model is verified with a dataset of 7481 reviews for four cruise alternatives. Finally, some comparisons, theoretical and practical implications are provided. Overall, this paper offers a comprehensive methodology for real-world group cruise evaluation, using online reviews from platforms like CruiseCritic as a form of collective wisdom to support decision-making. dc.description: The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
  • Editorial of the Special Issue on ‘New Trends in Intelligent Group Decision Making and Consensus Modelling’
    dc.title: Editorial of the Special Issue on ‘New Trends in Intelligent Group Decision Making and Consensus Modelling’ dc.contributor.author: Chiclana, Francisco; Dong, Yucheng; Herrera-Viedma, Enrique; Li, Cong-Cong; Zhang, Zhen dc.description: The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
  • Addressing the influence of limited tolerance and compromise behaviors on the social trust network consensus-reaching process
    dc.title: Addressing the influence of limited tolerance and compromise behaviors on the social trust network consensus-reaching process dc.contributor.author: Zhang, Hengjie; Liu, Shenghua; Li, Cong-Cong; Dong, Yucheng; Chiclana, Francisco; Herrera-Viedma, Enrique dc.description.abstract: In social trust network group decision-making, experts typically show limited tolerance and compromise behaviors when modifying their opinions to reach consensus. The first behavior implies that an expert will change their opinion without cost if the suggested opinion closely aligns with that of trusted experts. The second behavior implies that an expert will accept the suggested opinion only if it falls within a predefined compromise boundary relative to trusted experts’ opinions. However, existing maximum expert consensus models (MECMs) do not adequately consider these behaviors, limiting their practical applicability. To address this gap, this study proposes a social trust MECM with budget constraints. Budget constraints can lead to an insufficient number of experts within the consensus, underscoring the need for higher budget allocation to achieve consensus. To address this issue, a minimum cost consensus model (MCCM) considering network-dependent limited tolerance and compromise behaviors (NDLTCBs) was developed to provide a budget increment reference. Notably, network-dependent limited compromise behavior is crucial in the MCCM, especially when compromise values are small, as it may prevent feasible solutions. In such cases, a minimum compromise increment consensus model is created to determine the necessary increase in compromise values for a feasible MCCM solution. Subsequently, an interactive maximum expert consensus-reaching process is introduced. Simulation experiments demonstrate that consensus efficiency, in terms of the number of experts within the consensus, can be enhanced by considering NDLTCBs. dc.description: The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
  • Graph Model for Conflict Resolution With Internal Consensus Reaching and External Game
    dc.title: Graph Model for Conflict Resolution With Internal Consensus Reaching and External Game dc.contributor.author: Zhang, Hengjie; Wang, Fang; Dong, Yucheng; Chiclana, Francisco; Herrera-Viedma, Enrique dc.description.abstract: The graph model is devoted to game conflicts arising from incongruent pursued objectives among conflicting parties. Considering that each conflicting party is composed of multiple individuals, preference conflicts stemming from differing cognitive levels and knowledge backgrounds exist among internal individuals. This scenario simultaneously involving game conflicts and preference conflicts is termed dual conflict decision-making problem. Tailored to effectively address this problem, this study proposes an enhanced graph model that incorporates internal consensus and external stability. The best–worst method, incorporating comparative linguistic expressions, is devised to effectively elicit individual preferences over game states. To mitigate preference conflicts inherent to internal individuals within conflicting party concerning game states, a consensus reaching model minimizing preference information loss is introduced. By this way, collective preferences are obtained. Based on these, the concept of “game consensus” is proposed to manage the game conflicts and the diverse behaviors exhibited by conflicting party. Finally, a case study regarding price conflict within a dual-channel supply chain, accompanied by a comparative analysis, is presented to validate the effectiveness of the proposal. Compared to existing graph model, the proposal effectively grapples with consensus issues and heterogeneous behaviors within conflicting parties, making it more valuable in practice. dc.description: The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
  • Decayed Trust Propagation Method in Multiple Overlapping Communities for Improving Consensus Under Social Network Group Decision Making
    dc.title: Decayed Trust Propagation Method in Multiple Overlapping Communities for Improving Consensus Under Social Network Group Decision Making dc.contributor.author: Ji, Feixia; Wu, Jian; Chiclana, Francisco; Sun, Qi; Liang, Changyong; Herrera-Viedma, Enrique dc.description.abstract: This article proposes a decayed trust propagation method among multiple overlapping communities, and establishes a trust-driven consensus model for social network group decision making (SN-GDM). On the one hand, the use of overlapping nodes simplifies trust propagation by bridging complex connections among multiply overlapping communities. On the other hand, trust models' accuracy and realism are enhanced with the concept of trust decay, which accounts for the temporal dynamics of trust propagation. Thus, a first objective of this paper is to develop a trust propagation operator based on trust decay among multiple overlapping communities by leveraging overlapping nodes. By incorporating overlapping nodes' diverse trust relationships and perspectives, this approach allows to achieve reliable sources for generating recommendations in SN-GDM. A second objective of this paper is to design a decayed trust propagation induced consensus model to determine the optimal combination of overlapping nodes and feedback parameters, while balancing consensus efficiency and interaction willingness. The innovation of this approach is grounded in its ability to avoid excessive group adjustment to reach consensus. Numerical examples and comparative analysis demonstrate the model's performance in achieving efficient consensus under various representative recommendations. dc.description: The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
  • A bilateral negotiation mechanism by dynamic harmony threshold for group consensus decision making
    dc.title: A bilateral negotiation mechanism by dynamic harmony threshold for group consensus decision making dc.contributor.author: Cao, Mingshuo; Chiclana, Francisco; Liu, Yujia; Wu, Jian; Herrera-Viedma, Enrique dc.description.abstract: This article proposes a framework for bilateral negotiation mechanism to deal the case the concordant decision-makers (DMs) coalition cannot be constructed, which resolves the limitations of the existing group decision making methods. Bilateral negotiation means a process in which any two involved DMs change their own opinions based on each other’s opinions, avoiding the formation of group coalitions and the coercion of individual DMs. It can not only improve group consensus by interaction between individual DMs, but also considers the limited compromise behavior of DMs in the consensus bargaining process. The key contributions of this article contain: (1) It investigates the concept of ‘harmony threshold’ by combining the consensus levels of individual DMs and the number of group members to explain the limited compromise behavior of DMs. (2) it proposes a novel bilateral negotiation consensus mechanism with personalized compromise behavior with the group consensus threshold as the objective function and personalized harmony thresholds as constraints to help any two discording DMs partly to adopt each other’s opinions. And (3) It develops the ranking difference level (RDL) to measure the deviation degree between the final ranking of alternatives and all the DMs’ original rankings of alternatives. The research found that the proposed mechanism can reduce consensus cost by 40% and ranking difference by 5%. dc.description: The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
  • Evolution of Credit Scores of Enterprises in a Social Network: A Perspective Based on Opinion Dynamics
    dc.title: Evolution of Credit Scores of Enterprises in a Social Network: A Perspective Based on Opinion Dynamics dc.contributor.author: Liang, Haiming; Xu, Weijun; Chiclana, Francisco; Yu, Shui; Dong, Yucheng; Herrera-Viedma, Enrique dc.description.abstract: The use of social network to model the evolution of credit scores of networked enterprises is still a challenging task. This article develops an opinion dynamics model of the evolution of credit scores of enterprises in a social network. Firstly, based on the number of potential cooperated enterprises and the initial credit scores, the leader and follower enterprises are identified. Then, taking into consideration the cooperated benefit and discrimination cost, the cooperated utility between any two enterprises is calculated, which is used to compute the weights that one enterprise assigns to other enterprises. An opinion dynamics model on the evolution of credit scores of enterprises, inspired on the classical Friedkin–Johnsen’s social network model, is developed. Some desirable properties of the proposed opinion dynamics model are theoretically stated and proved. Finally, a numerical example is provided to illustrate the feasibility of the proposed opinion dynamics model, while a simulation analysis to investigate the joint influences of the connection probabilities and the network structure on the evolution of credit scores of enterprises is reported. dc.description: The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
  • Ordering vs. AHP. Does the intensity used in the decision support techniques compensate?
    dc.title: Ordering vs. AHP. Does the intensity used in the decision support techniques compensate? dc.contributor.author: Sáenz-Royo, Carlos; Chiclana, Francisco; Herrera-Viedma, Enrique dc.description.abstract: The manifestation of the intensity in the judgment of one alternative versus another in the peer comparison processes is a central element in some decision support techniques, such as the Analytical Hierarchy Process (AHP). However, his contribution in terms of quality (expected performance) with respect to the priority vector has not been evaluated so far. In this work, through the Intentional Bounded Rationality Methodology (IBRM) of Sáenz-Royo, Chiclana, and Herrera-Viedma (2023), the gains obtained from requiring the decision-maker to report an intensity judgment in pairs (AHP) are analyzed with respect to a technique that only requires expressing a preference (Ordering). The results show that when decision-makers have low levels of expertise, it is possible that a less informative and expensive technique (Ordering) performs better than a more informative and expensive one (AHP). When decision-makers have medium and high levels of expertise, AHP obtains meager gains about Ordering. This study proposes a cost-benefit analysis of decision support techniques contrasting the gains of a technique that requires more (AHP) resources with other less expensive (Ordering). Our results can change the way of managing the information obtained from experts’ judgments. dc.description: open access article

Click here to view a full listing of Enrique Herrera-Viedma's publications and outputs.

Research interests/expertise

  • Fuzzy preference modelling
  • Decision making problems with heterogeneous fuzzy information
  • Decision support systems, the consensus reaching process
  • Recommender systems, social networks
  • Modelling situations with missing/incomplete information
  • Rationality/consistency
  • Intelligent mobility and aggregation of information
  • Information retrieval
  • Bibliometrics analysis
  • Digital libraries.

Honours and awards

  • Best conference paper Awards:

S. Alonso, I.J. Pérez, E. Herrera-Viedma, F.J. Cabrerizo, Consensus with Linguistic Preferences in Web 2.0 Communities. 9th International Conference on Intelligent Systems Design and Applications (ISDA09), Pisa (Italy), 809-814, November 30 - December 2, 2009.

  • 2011 IEEE CIS TFS Outstanding Paper Award

F. Herrera, E. Herrera-Viedma, L. Martínez. A Fuzzy Linguistic Methodology To Deal With Unbalanced Linguistic Term Sets. IEEE Transactions on Fuzzy Systems 16:2 (2008) 354-370.

Membership of professional associations and societies

  •     Member of the European Society for Fuzzy Logic and Technology (EUSFLAT)
  •     IEEE member from 2012.

Conference attendance

PC membership

IFSA2009 / EUSFLAT09
FLINS2010 
FCTA 2013
AGOP2013
IFSA-NAFIPS 2013
ISDA'09 
ISKE2009 
ISKE2012
ITQM 2013
Multiconference CAEPIA 2013
UKCI2013
ICNC-FSKD 2013 

  • 28th International Conference on Artificial Intelligence. Application Stream (2008)
  • IEEE International Conference on Fuzzy Systems (2008)
  • IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (2009, 2011, 2013)
  • International Conference on Electronic Commerce and Web Technologies (2008)
  • Fuzzy Logic and Intelligent Technologies in Nuclear Science FLINS (2008, 2010)
  • IEEE Globecom Computer and Communications Network Security Symposium (2008,2009)
  • UK Workshop on Computational Intelligence (2008)
  • SGAI International Conference on Artificial Intelligence (2008)
  • EUROFUSE Workshop on Preference Modelling and Applications (2009, 2011)
  • Global Congress on Intelligent Systems (2009, 2010)
  • International Conference on Intelligent Systems and Knowledge Engineering (2009,2011)
  • International Conference on Fuzzy Computation (2009)
  • International Conference on Fuzzy Systems and Knowledge Discovery (2010)
  • International Symposium on Intelligent Decision Technologies (2010)
  • 2nd KES International Symposium on Intelligent Decision Technologies IDT'10 (2010)
  • 2011 International Conference onIntelligent Systems and Knowledge Engineering (2011)
  • 2009 International Fuzzy Systems Association WORLD CONGRESS (2009)
  • 2009 European Society for Fuzzy Logic and Technology CONFERENCE   (2009)
  • International Conference on Intelligent Systems Design and Applications (ISDA’09).

Externally funded research grants information

Intelligent systems for decisión making in heterogeneous contexts
Reference: Andalusian Excellence Project.TIC-5991
Period: November 2010 – June 2014

FUZZY-LING II: Fuzzy linguistic modelling of preferences: Applications in Information Retrieval and Group Decision Making.
Reference: Education Ministery. TIN2010-17876
Period: January 2011 – December 2013

Developing the fuzzy linguistic modelling and its use in web applications.
Reference: TIC-05299
Period: November 2009 – June 2013

FUZZY-LING: New fuzzy linguistic approaches for preference modelling:Applications on Information Retrieval and Decision Making
Project: Education Ministery. TIN2007-61079
Period: June 2007 - June 2011

Professional esteem indicators

Associate Editor

  • KNOWLEDGE BASED SYSTEMS
    From 2010
  • INFORMATION SCIENCES
    From 2010
  • SOFT COMPUTING 
    From 2012
  • JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 
    From 2012
  • FUZZY OPTIMIZATION & DECISION MAKING
    From 2013
  • IEEE Transactions on Systems, Man, and Cybernetics: Systems
    From 2013

Member of the Editorial Board:

  • FUZZY SETS AND SYSTEMS
    From 2007
  • SOFT COMPUTING 
    From 2007
  • INT. J. OF INFORMATION TECHNOLOGY AND DECISION MAKING
    From 2008
  • INT. J. OF COMPUTATIONAL INTELLIGENCE SYSTEMS
    From 2010

Journal Refereeing information

  • Annals of Operations Research
  • Applied Mathematical Modelling
  • Computers & Industrial Engineering
  • Data & Knowledge Engineering (DKE) Journal
  • European Journal of Operational Research
  • Fuzzy Sets and Systems
  • Group Decision and Negotiation
  • IEEE Transactions on Fuzzy Systems
  • IEEE Transactions on Industrial Informatics
  • IEEE Transactions on Systems, Man and Cybernetics, Part A
  • IEEE Transactions on Systems, Man and Cybernetics, Part B
  • IEEE Transactions on Systems, Man and Cybernetics, Part C
  • IMA Journal of Management Mathematics
  • Information Fusion
  • Information Sciences
  • International Journal of Approximate Reasoning
  • International Journal Artificial Intelligence in Medicine
  • International Journal of Computational Intelligence Research
  • International Journal of Information Technology & Decision Making
  • Journal of Intelligent and Fuzzy Systems
  • International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems(IJUFKS)
  • Journal of Environmental Management
  • Journal of Intelligent and Fuzzy Systems
  • Journal of Multiple-Valued Logic and Soft Computing
  • Journal of Operational Research Society
  • Journal of Systems Science and Systems Engineering
  • Knowledge-Based Systems 
  • Omega
  • Soft Computing
  • The Open Cybernetics and Systemics Journal.

Other Reviewing Activities

  • Switzerland National Council for Development and Innovation (2012)
  • Portuguese Foundation for Science and Technology (FCT) (2012 and 2013).