Ƶ

Professor Francisco Chiclana

Job: Professor of Computational Intelligence and Decision Making

Faculty: Computing, Engineering and Media

School/department: School of Computer Science and Informatics

Research group(s): Center for Computational Intelligence (CCI)

Address: Ƶ, The Gateway, Leicester, LE1 9BH UK

T: +44 (0)116 207 8413

E: chiclana@dmu.ac.uk

W:

 

Personal profile

Professor Francisco Chiclana received the B.Sc. and Ph.D. degrees in Mathematics, both from the University of Granada (Spain) in 1989 and 2000, respectively. He is currently a Professor of Computational Intelligence and Decision Making, and founder of DIGITS - Ƶ Interdisciplinary Group in Intelligent Transport Systems, Faculty of Technology, Ƶ (Leicester, UK). 

Professor Francisco Chiclana was the Coordinator of Ƶ submission for REF 2014 UOA 11: Computer Science and Informatics. 

Professor Chiclana has been Deputy Course Leader of the MScs in Computing, Information Technology, and Information Systems Management; Programme Tutor Years 1 and 2 of the BSc/HND/FD Business Information Technology. In 2013, Professor Chiclana co-developed the Doctoral Training Programme (DTP) in Intelligent Systems (IS) that he presently co-leads. Currently, he is Course Leader of BSc/MCOMP in Intelligent Systems (IS) and of MSc IS/ IS & Robotics (ISR).

Research group affiliations

  • CCI -    

Publications and outputs


  • 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.

  • 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.

  • dc.title: Reliability-driven large group consensus decision-making method with hesitant fuzzy linguistic information for the selection of hydrogen storage technology dc.contributor.author: Wang, Peng; Dong, Xin; Chen, Junhong; Wu, Xiaoming; Chiclana, Francisco dc.description.abstract: The use of hydrogen storage technology (HST) as a bridge for producing and utilizing hydrogen energy in the hydrogen industry chain is significant, and its evaluation has attracted the interest of researchers. Since there are different types of HSTs, selecting the most appropriate one requires the participation of plenty of experts with different professional backgrounds, which makes this be modeled as a large group decision-making problem. This paper develops a reliability-driven large group consensus decision-making (LGCDM) method for HST selection using the hesitant fuzzy linguistic terms set (HFLTS) as the evaluation representation format. Specifically, the expertise level of individuals and the reliability of group opinions are measured based on the set variables, and then the dimensionality of large groups is reduced based on the reliability of subgroup opinions. Furthermore, an opinion reliability rating mechanism is designed and, when consensus is not satisfactory, a feedback recommendation mechanism and consensus optimization mechanism are developed for implementation. Finally, the proposed reliability-driven LGCDM approach is applied to the HST selection for THVOW Company, and the comparison with existent related approaches indicates that it not only is practical and reasonable, but also provides a technical path for relevant departments to make decisions on practical issues.

  • dc.title: Minimum Cost Consensus-Based Social Network Group Decision Making With Altruism-Fairness Preferences and Ordered Trust Propagation dc.contributor.author: Feng, Yu; Dang, Yaoguo; Wang, Junjie; Du, Junliang; Chiclana, Francisco dc.description.abstract: Different from conventional decision-making environments, decision makers (DMs) in a community setting usually exhibit the complex social preferences and intricate social interactions, which may lead to high-decision costs for group consensus reaching. To address this challenge, we design a minimum cost consensus-based social network group decision making (SNGDM) approach considering altruism-fairness preferences and ordered trust propagation. First, a trust propagation method with order effect and path length is proposed to estimate the completed trust relationships among DMs in order to determine the weights of DMs. Then, inspired by the interaction of altruism and fairness preferences, we define the individual altruism-fairness preference utility function and utility level for cost consensus, and explore some properties. Afterwards, a new minimum cost consensus-based SNGDM with individual altruism-fairness preference utility is constructed. Finally, the validity of the proposed consensus framework is confirmed through the carbon reduction consensus problem of China’s aviation enterprises. Moreover, the sensitivity studies and comparative analysis are conducted to further demonstrate the merits of our proposal.

  • dc.title: Buildings' energy consumption prediction models based on buildings’ characteristics: Research trends, taxonomy, and performance measures dc.contributor.author: Al-Shargabi, Amal A.; Almhafdy, Abdulbasit; Ibrahim, Dina M.; Alghieth, Manal; Chiclana, Francisco dc.description.abstract: Building's energy consumption prediction is essential to achieve energy efficiency and sustain-ability. Building's energy consumption is highly dependent on buildings' characteristics such as shape, orientation, roof type among others. This paper offers a systematic literature review of studies that proposed building's characteristics based energy consumption prediction models. In particular, the paper reviews the types of buildings, their characteristics, the type of energy predicted, the dataset, the artificial intelligence (AI) methods used for energy consumption prediction, and the implemented research evaluation performance measures. The review findings show that a small number of studies consider buildings' characteristics as predictors for energy consumption. Most of the studies use historical energy consumption data, i.e., time-series data, to predict future buildings' energy consumption. The present study contributes a new taxonomy of the most common AI methods used for energy consumption predictions based on buildings' characteristics. The study also provides a comparative analysis of the different AI methods in terms of their contributions regarding the prediction of energy consumption. The review identifies research gaps in the existing studies, which is used to highlight future research directions.

  • 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.

  • dc.title: An endogenous and continual learning approach to personalize individual semantics to support linguistic consensus reaching dc.contributor.author: Wu, Yuzhu; Li, Zhaojin; Gao, Yuan; Chiclana, Francisco; Chen, Xia; Dong, Yucheng dc.description.abstract: In linguistic group decision making, it is known that decision makers are individualized in understanding the meanings of words, i.e., decision makers have personalized individual semantics (PISs) in the representation of linguistic preferences. Since individuals influence each other mutually in the consensus reaching process, PISs will accordingly change. This suggests that there is an updating process of PISs for individuals. This paper proposes an endogenous and continual learning-based approach to update PISs in consensus reaching process by incorporating the endogenous consistency-driven PIS model and continual PIS learning based consensus model. Through this approach, individuals’ PISs are endogenously updated and learned while ensuring an optimal level of consistency and an increased level of collective consensus during consensus reaching process. At the end of the study, numerical examples and some simulation and comparative analyses are presented to justify the effectiveness of proposed approach 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.

  • 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.

  • dc.title: Dynamic Compromise Behavior Driven Bidirectional Feedback Mechanism for Group Consensus With Overlapping Communities in Social Network dc.contributor.author: Gai, Tiantian; Wu, Jian; Chiclana, Francisco; Cao, Mingshuo; Yager, Ronald R. dc.description.abstract: In social network group decision making (SN-GDM), overlapping communities are special community structures that can assist opinion interaction to reach group consensus. However, the specific mechanisms of how overlapping structures facilitate community interaction need to be further explored. In addition, the compromise behavior of decision makers (DMs) is conducive to group consensus, but it is usually fixed at the same value, and then it need further research the characteristic of the dynamics compromise limits. To this end, the overlapping community structures under DMs’ trust network is detected. Then, the effect of community overlap in social networks on community interaction is explored. Meanwhile, a limited compromise function is built based on prospect theory to describe the dynamic compromise behavior of communities. Hence, a dynamic compromise behavior driven bidirectional feedback mechanism with overlapping communities is proposed in the context of SN-GDM, and an illustrative example with comparative analysis is provided to testify the advantages of proposed method. It is proved that overlapping communities can improve the compromise willingness compared to nonoverlapping communities, indicating that overlapping communities can serve as a bridge to facilitate interaction, and the dynamic compromise behavior can more realistically describe the real behavior of DMs. In general terms, the proposed method provides a solution to the consensus reaching issue of SN-GDM from a new perspective. Specifically, it can be applied to real-life application scenarios, such as group recommendation to recommend acceptable solutions for social network group users. 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.

  • dc.title: A tolerance index based non-cooperative behaviour managing method with minimum cost in social network group decision making dc.contributor.author: Sun, Qi; Wu, Jian; Chiclana, Francisco; Ji, Feixia dc.description.abstract: This paper introduces a novel consensus theoretical framework designed to effectively manage non-cooperative behavior in social network group decision making (SNGDM). It addresses the challenge by considering both individuals’ willingness to adjust preferences and the associated costs of achieving consensus. To deal with this issue, the personalized individual semantics (PIS) model is employed to handle original evaluation matrices by converting linguistic terms into numerical values based on experts’ personalized opinions. Subsequently, a tolerance index (TI) is defined to reflect the willingness of experts to adjust their preferences. An improved minimum cost (MC) feedback model based on TI is established. The novelty of the proposed approach is that its integration of individual preference adjustment willingness and consensus efficiency, effectively preventing groupthink. In addition, a maximum group consensus degree optimisation model is proposed to detect non-cooperative behaviour of experts. To ensure an optimal solution for the minimum cost feedback model, a weight update method is proposed, considering the trust relationship between experts. A detailed analysis regarding the selection of tolerance thresholds to prevent over-penalisation of weights of non-collaborators is reported. Finally, comprehensive numerical and comparative analyses are presented to validate the proposed method. 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.


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Key research outputs

F. Chiclana, E. Herrera-Viedma, S. Alonso, F. Herrera:  IEEE Transactions on Fuzzy Systems 17 (1), 14-23, February 2009. doi:10.1109/TFUZZ.2008.928597

S. -M. Zhou, F. Chiclana, R. I. John, J. M. Garibaldi:  Fuzzy Sets and Systems 159 (24), 3281-3296, December 2008. doi:10.1016/j.fss.2008.06.018 

S-M. Zhou, F. Chiclana,R. John, J. M. Garibaldi:  IEEE Transactions on Knowledge and Data Engineering 23 (10) 1455-1468, October 2011. doi: 10.1109/TKDE.2010.191

F. Herrera, E. Herrera-Viedma, S. Alonso, F. Chiclana:  Fuzzy Optimization and Decision Making 8, 337-364, 2009 (ISSN: 1568-4539). doi: 10.1007/s10700-009-9065-2

Patrizia Pérez-Asurmendi, F. Chiclana:  Applied Soft Computing 18, May 2014, Pages 196–208. doi: 10.1016/j.asoc.2014.01.010

F. Chiclana, J. M. Tapia-Garcia, M. J. del Moral, E. Herrera-Viedma:  Information Sciences 221, 110-123, February 2013, doi: 10.1016/j.ins.2012.09.014

Jian Wu, F. Chiclana:  Knowledge-Based Systems 59, March 2014, Pages 97–107. doi: 10.1016/j.knosys.2014.01.017

S. Greenfield, F. Chiclana, S. Coupland, R. I. John:  Information Sciences 179(13), 2055-2069, June 2009. doi: 10.1016/j.ins.2008.07.011

S. Greenfield, F. Chiclana, R. John, S. Coupland:  Information Sciences 189, 77-92, April 2012. doi: 10.1016/j.ins.2011.11.042

E. Herrera-Viedma, F. Herrera, F. Chiclana , M. Luque:  European Journal of Operational Research 154(1), 98-109, April 2004. doi:10.1016/S0377-2217(02)00725-7

F. Chiclana, F. Herrera, E. Herrera-Viedma:  Fuzzy Sets and Systems 97(1), 33-48, July 1998. doi:10.1016/S0165-0114(96)00339-9 

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. 

Areas of teaching

I have a lot of teaching experience that I have acquired over the past 21 years as a secondary school teacher of mathematics (Granada, Montoro-Cordoba, Estepona and Mabella - Malaga) in Spain (September 1990 - July 2003), and at Ƶ (August 2003 - present) lecturing different modules at undergraduate, postgraduate (MSc) and PhD levels (see list below). Previously, I worked as a temporary lecturer at the Department of Algebra, University of Granada, in Spain (January 1990-March 1990) teaching calculus and financial mathematics to first year students of management studies.

In June 2005, I completed the HEA accredited programme for staff new to teaching in Higher Education which entitled me to registered practitioner status of the Higher Education Academy. Certificate presentation was on 28th September 2005 by the Director of Human Resources. I was glad to have Dr Jenny Carter as my mentor during my first 2 years at Ƶ. Currently, I am a fellow of the Higher Education Academy.

I was nominated by students for a Vice-Chancellor's Distinguished Teaching Award in 2009. The students think highly of me and my contribution to the student experience is valued as the following quotation testifies:

"He willingly devotes time to listen to any student and has helped me to achieve good mark. He is consistently excellent communicator, stimulating and informative..."         

 

Areas of Teaching:
  • Mathematics for Computing
  • Financial Mathematics
  • Statistics
  • Research Methods
  • Fuzzy Logic

 

Qualifications

  • Certificate Successful completion of HEA accredited pathway for staff new to teaching in Higher Education, Ƶ, Leicester, UK (September 2005)
  • Outstanding Award for a PhD in Mathematics for the academic year 1999/2000, University of Granada, Spain (27 November 2002)
  • PhD in Mathematics (Distinction Cum Laude), Department of Computer Science and Artificial Intelligence, University of Granada, Spain (24 March 2000)
  • Public examination to become part of government civil service as a secondary school teacher, Ministry of Education and Science, Spanish Government (July 1990)
  • Degree in Mathematics (Statistics & Operational Research), University of Granada, Spain (1984-1989)
  • Certificate of Pedagogic Aptitude, Institute of Educational Science, University of Granada, Spain (1989).

Ƶ taught

Undergraduate

CSCI1004 - Mathematics for Computing (2003-2004)
MGSC1102 - Modelling for Management Decisions 1 (2003-2004)
INFO1007 - Introduction to Business Computing (2003-2004)
INFO1407 - Introduction to Business Computing (2004-2007)
MATH2211 - Information Systems (2003-2005)
COMP2006 - Research in Computing (2004-2008)
CSCI1412 - Computer Technology (2007-2010)
Industrial Placement Visit Tutor (2003-2012)
IMAT1901: Quantitative Methods (2010-2012)
IMAT2701: HND BIT Project (2009-2012)
IMAT3451 - Final Year Project Supervisor (2003-2012)

Postgraduate

IMAT5119 - Fuzzy Logic (2004-2012)
IMAT5120 - Research Methods (2004-2012)
IMAT5314 - MSc Project (2010-2012)

PhD Level

PhD Course: Typesetting Documents with LaTeX (2004-2012)  

Honours and awards

Outstanding Award for a PhD in Mathematics for the academic year 1999/2000, University of Granada, Spain (27 November 2002).

Third prize in Ƶ’s Creative Thinking Awards 2010, for the Greenfield-Chiclana Collapsing Defuzzifier.

Finalist for 1st Ƶ - THE OSCAR AWARDS  in category: Outstanding Contribution to Research Excellence (2012).

Membership of external committees

Fellow of the Higher Education Academy, UK

Member of the European Society for Fuzzy Logic and Technology (EUSFLAT) 

Current research students

Current:

  • Maria Raquel Ureña Perez, University of Granada (Spain)- Department of Computer Science and Artificial Intelligence (DECSAI), University of Granada. January 2012. Co-supervisor: Prof. Enrique Herrera-Viedma
  • Manal Alghieth (Ƶ) - Second supervisor. First supervisor: Dr Yingjie Yang (CCI). Mode of study: Full -time on site (01/04/2012)
  • Simon Witheridge (Ƶ) - Intelligent Transport Systems: Integrated Traffic Management Control. First supervisor. Second supervisors: Dr Benjamin Passow (DIGITS) and Dr David Elizondo (DIGITS). Mode of study: Full -time on site (01/10/2012). Change to second supervisor and Ben Passow first supervisor from 01-October-2013.
  • Eseosa Oshodin (Ƶ) - Decentralised Mechanism for REcommender/Reputation System: A Case Study on Trust. First supervisor. Second supervisors: Dr Samad Ahmadi (VirAL/CCI). Mode of study: Full -time on site (01/10/2013).
  • Salim Hasshu (Ƶ) - Smart, Green and Integrated Transport - Personalised traffic health planner. First supervisor. Second supervisors: Dr Benjamin Passow (DIGITS) and Dr David Elizondo (DIGITS). Mode of study: Full -time on site (01/10/2013).

Completed:

  • Dr Sergio Alonso Burgos, University of Granada (Spain)- Group Decision Making With Incomplete Fuzzy Preference Relations. Department of Computer Science and Artificial Intelligence (DECSAI), University of Granada. May 2006. Co-supervisors: Prof. Enrique Herrera-Viedma, Prof. Francisco Herrera.
  • Dr Fahad Alshathry (Ƶ) - Building a Decision Support System to integrate digital evidence with interview investigation. Second supervisor. August 2011. First supervisor: Dr Giampaolo Bella (STRL).
  •  - Type-2 Fuzzy Logic: Circumventing the Defuzzification Bottleneck. First supervisor. Second supervisors: Prof. Robert I. John and Dr Simon Coupland (CCI). May 2012.
  • Tamas Galli (MPhil Ƶ) - Fuzzy Logic Based Software Product Quality Models by Execution Tracing. First supervisor. Second supervisor: Dr Jenny Carter (CCI). Technical adviser: Helge Janicke (STRL). Mode of study: Part -time distance International PhD Programme (01/03/2011). February 2014.

Externally funded research grants information

  • Awarded Campus de Excelencia GENIL-BioTIC-UGR Research Visit Grant (1 week) by the University of Granada (Spain). Principal Investigator. €1000. Period: February 2014.
  • Awarded Campus de Excelencia GENIL-BioTIC-UGR Research Visit Grant (1 week) by the University of Granada (Spain). Principal Investigator. €1200. Period: June 2012.
  • Awarded University of Granada Research Visit Grant by the Regional Government of Andalucia (Spain). Principal Investigator. €3184. Period: June 2009 - August 2009.
  • Awarded research funding from the EPSRC for a 3 year projet, which extends my previous work investigating the role of fuzzy logic in aggregation and consensus modelling. Towards a Framework for Modelling Variation, EPSRC, UK, Co-investigator. £145K. Period: 2006 - 2009.
  • Awarded a Royal Academy of Engineering grant support towards my research networking visit to Spain. 2009.
  • Awarded 2 Conference Grants (Royal Society and Royal Academy of Engineering) to disseminate my research findings at IPMU 2006 and FUZZ-IEEE 2008.
  • External research collaborator in Spanish Government Research Projects lead by my collaborators.
  • Linguistic Information in Decision Making Analysis Processes. Preference Modelling and Applications. Spanish Department for Education and Culture, Co-investigator. €91K. Period: 01/01/2010 to 31/12/2012.  
  • Project of Excellence: Developing the Fuzzy Linguistic Model and its Use in WEB Applications. Regional Government of Andalucia (Spain), Co-investigator. €187K. Period: 01/01/2009 to 31/12/2013.
  • Decision Models with Uncertainty in Heterogeneous Contexts. Application to Evaluation Processes in On-line Environments. Spanish Department for Education and Culture, Co-investigator. €50K. Period: 01/01/2007 to 31/12/2009.
  • Project of Excellence: Development of WEB Information Access Systems Based on Artificial Intelligence Techniques (SAINFOWEB). Regional Government of Andalucia (Spain), Co-investigator. €50K. Period: 01/01/2005 to 31/12/2008.
  • An Information System for the Quality of Aerial Transportation Based on Artificial Intelligence Techniques and Oriented Towards the Citizen. Spanish Department of Transport, Co-investigator. €96K. Period: 01/01/2005 to 31/12/2008.
  • Flexible Preference Modelling in Decision Making. Applications in online recommender systems (I) and (II). Spanish Department for Education and Culture, Co-investigator. €33K. Period: 01/01/2003 to 31/12/2006.
  • Spanish National Network in Decision Making, Preference Modelling and Aggregation (I) and (II). Spanish Department for Education and Culture, Co-investigator. €30K. Period: 01/01/2004 to 31/12/2006.
  • Similarities Between Physics and Mathematics in Secondary Education. Regional Government of Andalucia (Spain), Principal Investigator. €700. Period: 01/09/2002 to 30/06/2003.

 

Internally funded research project information

  • Awarded Ƶ Research Scholarship 2013-14 scheme for 3 years starting from October 2013. This scheme provides for funding to cover both fees and stipend equivalent to the RCUK standard rate (£13,770 for 2012-13) to support one research student from UK or EU. (Principal Investigator with Dr David Elizondo and Dr Benjamin Passow - DIGITS).
  • Awarded Ƶ Research Scholarship 2012-13 scheme for 3 years starting from October 2012.  This scheme provides for funding to cover both fees and stipend equivalent to the RCUK standard rate (£13,770 for 2012-13) to support one research student from UK or EU. (PI with Dr David Elizondo and Dr Benjamin Passow - DIGITS).
  • Awarded Ƶ Revolving Investment Fund (RIF) for Research for the project DIGITS: De Montfort Interest Group In Transport Systems. Principal Investigator. £10K. Period: January 2012 - July 2012. 
  • Awarded £4K under the Faculty of Computing Sciences and Engineering (Ƶ) Pump Priming initiative to promote external collaborations at the University of Granada and the University of Jaen in Spain. 2005.

Professional esteem indicators

Associate Editor and Editorial Board

International journals in 

  • Associate Editor of  (from April 2014).
  • Associate Editor of  (from April 2014) (Member of the Editorial Board from October 2011 to March 2014).

  • Member of the Editorial Board of  (from February 2014).

  • Member of the Advisory Board of  (from December 2013).

  • Member of the Editorial Board of Journal of Multiple-Valued Logic and Soft Computing (Old City Publishing) ISSN: 1542-3980 (from August 2011).

  • Associate Editor of  (from September 2012).

  • Member of the Editorial Board of  (from July 2012).

  • Member of the Editorial Board of  (February 2013).

International journals not in ISI Web of Knowledge

  • Associate Editor of Journal of Signal Processing Theory and Applications (Columbia International Publishing) ISSN: 2163-2278 (from December 2011).
  • Member of the Editorial Board of  (from October 2007).

Guest Editor for international journals in ISI

  •  in the International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (IJUFKS), Volume 16, Issue 2 Supp. August 2008. F. Chiclana, E. Herrera-Viedma, S. Alonso, F. Herrera (Eds.).
  • "COMPUTING WITH WORDS IN DECISION MAKING" in the International Journal of Fuzzy Optimization and Decision Making Journal, Volume 8, Number 4 / December 2009. F. Herrera, E. Herrera-Viedma, S. Alonso and F. Chiclana (Eds.). 

Research Council Reviewer and External Examiner

UK

  • EPSRC
  • The Royal Society

International

  • The Research Foundation - Flanders (Belgium) (Fonds Wetenschappelijk Onderzoek - Vlaanderen, FWO)
  • The Romanian National Council for Development and Innovation
  • Portuguese Foundation for Science and Technology (FCT)
  • Austrian Science Fund (FWF)
  • Netherlands Organisation for Scientific Research, Division of Social Sciences.

PhD external examiner

  • Univ. Granada (Granada, Spain)
  • Univ. Jaén (Jaén, Spain)
  • Ulster University (Belfast, UK)
  • University of Valladolid (Valladolid, Spain)
  • École Supérieure d'Électricité (SUPÉLEC, Paris, France).

Conference Organisation, Plenary Talks and Invited Lectures

  • Co-chair of 

Organised and Chaired special sessions in the following international conferences:  

  • in FUZZ-IEEE 2014 - Beijing (China) that will be held as part of the  from 6-11 July 2014.
  •  in the  that will be held in Moscow - Russia from 3-5 June 2014.
  • Focus Session on Consensus and Decision Making Under Uncertainty in the 2013 IFSA World Congress NAFIPS Annual Meeting Edmonton, Canada June 24-28, 2013.
  • Special Session on Fuzzy Preference Modelling, Decision Making and Consensus in first International Conference of Information Technology and Quantitative Management (ITQM 2013), May 16-18, 2013 at Suzhou, China.
  • Special Session on "Fuzzy Approaches in Preference Modelling, Decision Making and Applications" for the IEEE International Conference on Fuzzy Systems (FUZZ_IEEE), London, UK (2007).
  • Special Session on "Soft Decision Making - Theory and Applications" for the IEEE International Conference on Fuzzy Systems (FUZZ_IEEE), Hong-Kong, China (2008).
  • Special Session on "Fuzzy Decision Making Issues: Preference Modelling and Aggregation" for the 8th International FLINS Conference on Computational Intelligence in Decision and Control, Madrid, Spain (2008).
  • Organised Workshop on "Type-2 Fuzzy Logic and the Modelling of Uncertainty" at the AI-2007 Twenty-seventh SGAI International Conference on Artificial Intelligence, Cambridge, UK.
  • Plenary talk at the 2009 EUROFUSE Workshop on Preference Modelling and Decision Analysis.
  • Invited Lectures at the University of Granada, the University of Pamplona, the University of Valladolid, the University of Castilla-La Mancha in Albacete, the University of Jaen (Spain), Ghent University (Belgium) and University of Portsmouth (UK).
  • Programme committee member of more than 50 international conferences.
Francisco-Chiclana