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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: 蜜桃直播, The Gateway, Leicester, LE1 9BH UK

T: +44 (0)116 207 8413

E: chiclana@dmu.ac.uk

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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 - 蜜桃直播 Interdisciplinary Group in Intelligent Transport Systems, Faculty of Technology, 蜜桃直播 (Leicester, UK). 

Professor Francisco Chiclana was the Coordinator of 蜜桃直播 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: A GRA-based heterogeneous multi-attribute group decision-making method with attribute interactions dc.contributor.author: Feng, Yu; Dang, Yaoguo; Wang, Junjie; Du, Junliang; Chiclana, Francisco dc.description.abstract: In the era of VUCA (Volatility, Uncertainty, Complexity, Ambiguity), multi-attribute group decision-making (MAGDM) problems face the challenges of heterogeneous uncertainty in decision information and complex interactions between attributes, which greatly affect the reliability of decision-making outcomes. To address these challenges, this paper proposes a novel heterogeneous MAGDM method based on grey relational analysis (GRA) that considers attribute interactions. First, the heterogeneous information is integrated, including crisp numbers, generalized grey numbers, intuitionistic fuzzy numbers, hesitant fuzzy numbers, and probabilistic linguistic term sets. Then, by incorporating the 2-additive Choquet integral into GRA, we establish a heterogeneous grey interactive relational model and explore its properties. Subsequently, a heterogeneous grey relational Mahalanobis-Taguchi System is designed to estimate the Shapley values of attributes. Additionally, a two-stage resolution mechanism, comprising a consensus reaching process followed by a grey relational multi-objective programming model, is devised to determine the interaction indices. Finally, the effectiveness of the proposed method is demonstrated through a case study from China鈥檚 aviation manufacturing industry, along with sensitivity analysis and comparison analyses. 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: The value of expert judgments in Decision Support Systems dc.contributor.author: S谩enz-Royo, Carlos; Chiclana, Francisco dc.description.abstract: It is a challenge to improve a decision support system (DSS) based on expert judgments; the literature proposes to improve accuracy and performance by increasing the sophistication and complexity of the DSS, but at what cost? This study presents a model for encoding a DSS based on expert judgments and evaluating its efficiency, establishing a three-part analysis structure: information requirements (number of judgments), quality requirements (quality assurance mechanisms), and algorithmic complexity. With a focus on the cost of judgments, a systematic and quantitative coding of the performance and cost in each part of the DSS is established. A 鈥渂reak-even point鈥� efficiency measure, defined as the maximum percentage of the optimal performance that can be paid per unit of resources, is proposed to ensure that the use of the DSS remains profitable. Counterintuitively, the results of a case study show that the efficiency of DSSs does not necessarily increase with respect to the informativeness level of DSSs. Overall, this study provides a new method for evaluating the efficiency of DSSs. 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: Personalized trust incentive mechanisms with personality characteristics for minimum cost consensus in group decision making dc.contributor.author: Xing, Yumei; Wu, Jian; Chiclana, Francisco; Wang, Sha; Zhu, Zhaoguang dc.description.abstract: Traditional group decision making is usually to force inconsistent decision-makers (Namely, decision makers whose consensus degree does not reach a predefined level/consensus threshold.) to revise their opinions in order to improve the group consensus level. But decision-makers with conservative, neutral and radical behaviors differ in the extent to which they adjust their opinions. Hence, this paper investigates a personalized trust incentive mechanisms with personality characteristics for minimum cost consensus in group decision making, including opinion incentive and trust incentive. Firstly, the trust-driven personalized incentive mechanisms for personality characteristics, such as conservative, neutral and radical, are established to improve the adoption intention of decision makers. And then, the trust incentive evolution model with personality characteristics is established to reveal that the trust held by the remaining group members towards conservative decision makers is stable, the trust towards neutral decision makers is enhanced, and the trust towards radical decision makers is weakened. Further, the minimum cost consensus model based on personalized trust incentive mechanism with personality characteristics is constructed to generate feedback opinions of these decision makers within their respective adjustment ranges, exploring the influence law of consensus efficiency in decision makers with different personality characteristics. Finally, an illustrative example on supplier selection in the cruise ship manufacturing industry is provided to demonstrate the rationality and superiority of 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.

  • dc.title: A novel bi-objective R-mathematical programming method for risk group decision making dc.contributor.author: Tang, Guolin; Fu, Runqing; Seiti, Hamidreza; Chiclana, Francisco; Liu, Peide dc.description.abstract: Most risk-based multi-attribute group decision-making (R-MAGDM) frameworks often assume that attributes are independent and rarely consider the decision-maker鈥檚 (DM) psychological behaviours. However, in many cases, attributes tend to interact with each other, and DMs often display bounded rationality during the decision-making process. A new R-mathematical programming method is developed to address these issues by integrating R-sets, regret theory, the Banzhaf function, and the LINMAP method. Initially, a novel exp operation and a method for defuzzification of R-numbers are introduced, enabling the utilisation of R-numbers in decision-making problems. Subsequently, an R-utility function and an R-regret/rejoice function are defined to calculate the Banzhaf R-perceived utility of each alternative. Following this, R-group consistency (RGCI) and inconsistency indexes (RGII) are introduced for pair-wise rankings of alternatives. Furthermore, a bi-objective R-programming model is formulated to maximise RGCI and minimise RGII to identify the R-ideal solution and optimal weights of criteria and DMs. An optimisation algorithm utilising the non-dominated sorting genetic algorithm-II (NSGA-II) is proposed to solve the constructed model and obtain the non-dominated set. Four decision-making schemes are presented to determine the best trade-off solution from this non-dominated set. Finally, a numerical case is presented to demonstrate the proposed approach鈥檚 practicality, effectiveness, and superiority. 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: Enhancing train travel time prediction for China鈥揈urope railway express: A transfer learning-based fusion technique dc.contributor.author: Guo, Jingwei; Guo, Jiayi; Fang, Lin; Chen, Zhen-Song; Chiclana, Francisco dc.description.abstract: Accurate train travel time (T-t) is crucial for the quality and reliability of rail transport services, particularly for China鈥揈urope Railway Express (CRE), which occupies an important position in the global transportation network. Despite transfer learning being a useful technique to address the limited data in CRE train travel time prediction, it struggles with some insurmountable problems, such as the inability to handle seasonality and non-stationarity of data. Therefore, this paper proposes a novel fusion technique that combines transfer learning, wavelet transform, and meta-learning for predicting CRE travel time with a limited amount of sample data. Specifically, transfer learning is employed to overcome data limitations in constructing machine learning models for predicting CRE travel time. Meanwhile, a wavelet transform time series decomposition is designed to reveal hidden patterns in data and improve comprehensibility and predictability. For task decomposition, a multi-task meta-learning method is proposed that obtains the loss function gradient for each task and then updates model parameters to achieve the overall optimal structure. Lastly, a fusion technique model named WT_T.R2_MAML is developed to integrate the aforementioned functions. Through the analysis of actual operational data from the CRE trains, we have validated the successful integration of the WT_T.R2_MAML model. This achievement outlines a roadmap for the future implementation of fusion technologies. 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 dynamic trust and prospect theory driven bilateral feedback mechanism for maximizing consensus income in social network group decision making dc.contributor.author: Zhu, Zhaoguang; Zhang, Xiang; Cao, Mingshuo; Chiclana, Francisco; Wu, Jian dc.description.abstract: This article proposes a prospect theory-based bilateral feedback mechanism with dynamic trust to reach group consensus under social network. A trust evolution model is developed by the concept of trust gap to reflect the dynamic changes in the trust relationships between DMs. The concept of a loss prospect threshold is then proposed, combining dynamic trust and consensus index, to quantitatively describe the maximum acceptable psychological loss for DMs in each round of feedback. Additionally, two indexes are defined to study feedback behavior: the improvement of consensus level as an income prospect and the preference adjustment as a loss prospect. Therefore, a bilateral feedback optimization model is constructed by maximizing the consensus income prospect under the limitation of the loss prospect threshold. To explore the role of dynamic trust and psychological behavior on the consensus-reaching process, three different feedback mechanisms are designed and compared with the proposed model, demonstrating that the proposed model can reduce preference adjustment costs and improve satisfaction with the final decision. A numerical example with sensitivity analysis of parameters is provided to illustrate the feasibility of the proposed model. 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 dynamic cost compensation mechanism driven by moderator preferences for group consensus in lending platforms dc.contributor.author: Meng, Yanli; Wang, Li; Chiclana, Francisco; Yang, Haijun; Wang, Sha dc.description.abstract: The matching service the lending platform (moderator) provides acts as a facilitative conduit for reaching a loan consensus, facilitating agreements among multiple lenders and borrowers (decision makers). In light of the reality that decision-makers exhibit varying sensitivities to compensation expectations in response to opinion adjustment, the moderator鈥檚 demonstration of a preferred compensation mechanism determines the efficiency of the matching service. This article proposes a dynamic cost compensation mechanism driven by moderator preferences for group consensus in lending platforms. Firstly, the utility function describes adjusters鈥� preferences, defining three unit cost compensation preferences: Power-type I, II and right-partial S-shaped preferences. Subsequently, we construct a generalized dynamic minimum-cost consensus decision model to determine the optimal unit compensation strategies within the opinion interval delineated by the moderator. For the likelihood of equitable concerns arising from fluctuations in unit compensation costs, we enforce the fairness of the compensation strategy by incorporating the Gini coefficient as a constraint within the consensus model. To validate the effectiveness and applicability of the proposed models, we apply the proposed models to online lending utilizing data obtained from an online peer-to-peer lending platform. 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 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鈥� 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鈥檚 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.

  • dc.title: A self-esteem driven feedback mechanism with diverse power structures to prevent strategic manipulation in social network group decision making dc.contributor.author: Sun, Qi; Zhang, Xiang; Chiclana, Francisco; Ji, Feixia; Long, Qingqi; Wu, Jian dc.description.abstract: In social network group decision-making (SNGDM), the distribution of power structures and strategic manipulation behaviors pose challenges to the fairness and efficiency of the decision-making process. This paper introduces a novel consensus theoretical framework, specifically designed for analyzing power structures and preventing strategic manipulation behavior in SNGDM. It proposes a centrality measures-based influence index and a structural holes and graph density-based power index, respectively, to identify opinion leaders and power dynamics of subgroups in social trust networks. Then, a maximum entropy-based model is presented to explore power dynamics for preference aggregation in SNGDM. Furthermore, this paper introduces a feedback model based on the boundary maximum consensus degree, addressing issues that existing consensus methods tend to overlook, including the self-esteem of decision-makers and the risks of manipulation behavior. The model considers the self-esteem of subgroups when adjusting preferences, aiming to prevent potential strategic manipulation and enhance the fairness and efficiency of decision-making. Finally, thorough numerical evaluations and comparative assessments have been conducted to substantiate the effectiveness of the proposed methodology. Experiment results show that concentrated power can speed up consensus formation but may harm fairness, while dispersed power, although it slows consensus, increases participation and diversity, reducing the risk of power abuse. 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: 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鈥損ersonalized helpfulness level (IHL鈥揚HL) model is devised to evaluate review helpfulness, considering not only inherent review quality but also personalized relevance to the specific DMs鈥� contexts. Leveraging deep learning techniques like Sentence-BERT and neural networks, the IHL鈥揚HL 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.


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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 蜜桃直播 (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 蜜桃直播. 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, 蜜桃直播, 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).

蜜桃直播 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 蜜桃直播’s Creative Thinking Awards 2010, for the Greenfield-Chiclana Collapsing Defuzzifier.

Finalist for 1st 蜜桃直播 - 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 (蜜桃直播) - Second supervisor. First supervisor: Dr Yingjie Yang (CCI). Mode of study: Full -time on site (01/04/2012)
  • Simon Witheridge (蜜桃直播) - 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 (蜜桃直播) - 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 (蜜桃直播) - 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 (蜜桃直播) - 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 蜜桃直播) - 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 蜜桃直播 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 蜜桃直播 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 蜜桃直播 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 (蜜桃直播) 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