A consensus model for group decision making problems with linguistic interval fuzzy preference relations

Sometimes, we find decision situations in which it is difficult to express some preferences by means of concrete preference degrees. In this paper, we present a consensus model for group decision making problems in which the experts use linguistic interval fuzzy preference relations to represent their preferences. This model is based on two consensus criteria, a consensus measure and a proximity measure, and on the concept of coincidence among preferences. We compute both consensus criteria in the three representation levels of a preference relation and design an automatic feedback mechanism to guide experts in the consensus reaching process.

[1]  F. Herrera,et al.  A linguistic decision process in group decision making , 1996 .

[2]  Jui-Fang Chang,et al.  An Approach to Group Decision Making Based on Incomplete Linguistic Preference Relations , 2009, 2009 Fifth International Conference on Information Assurance and Security.

[3]  Zeshui Xu,et al.  Interval multiplicative transitivity for consistency, missing values and priority weights of interval fuzzy preference relations , 2010, Inf. Sci..

[4]  Enrique Herrera-Viedma,et al.  Group decision making problems in a linguistic and dynamic context , 2011, Expert Syst. Appl..

[5]  Enrique Herrera-Viedma,et al.  A Consensus Model for Group Decision Making Problems with Unbalanced Fuzzy Linguistic Information , 2009, Int. J. Inf. Technol. Decis. Mak..

[6]  Francisco Herrera,et al.  Direct approach processes in group decision making using linguistic OWA operators , 1996, Fuzzy Sets Syst..

[7]  Enrique Herrera-Viedma,et al.  A Linguistic Multi-Criteria Decision Making Model Applied to the Integration of Education Questionnaires , 2011, Int. J. Comput. Intell. Syst..

[8]  Francisco Herrera,et al.  Linguistic decision analysis: steps for solving decision problems under linguistic information , 2000, Fuzzy Sets Syst..

[9]  Enrique Herrera-Viedma,et al.  A Model Based on Fuzzy Linguistic Information to Evaluate the Quality of Digital Libraries , 2010, Int. J. Inf. Technol. Decis. Mak..

[10]  Lotfi A. Zadeh,et al.  The Concepts of a Linguistic Variable and its Application to Approximate Reasoning , 1975 .

[11]  Zeshui Xu,et al.  A method for multiple attribute decision making with incomplete weight information in linguistic setting , 2007, Knowl. Based Syst..

[12]  Zeshui Xu,et al.  Some models for deriving the priority weights from interval fuzzy preference relations , 2008, Eur. J. Oper. Res..

[13]  Luis Martínez-López,et al.  A Consensus Support System Model for Group Decision-Making Problems With Multigranular Linguistic Preference Relations , 2005, IEEE Transactions on Fuzzy Systems.

[14]  S. Orlovsky Decision-making with a fuzzy preference relation , 1978 .

[15]  Ronald R. Yager,et al.  On ordered weighted averaging aggregation operators in multicriteria decision-making , 1988 .

[16]  Enrique Herrera-Viedma,et al.  A Mobile Decision Support System for Dynamic Group Decision-Making Problems , 2010, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[17]  Enrique Herrera-Viedma,et al.  Dealing with incomplete information in a fuzzy linguistic recommender system to disseminate information in university digital libraries , 2010, Knowl. Based Syst..

[18]  Enrique Herrera-Viedma,et al.  A model of an information retrieval system with unbalanced fuzzy linguistic information: Research Articles , 2007 .

[19]  Francisco Herrera,et al.  Incorporating filtering techniques in a fuzzy linguistic multi-agent model for information gathering on the web , 2004, Fuzzy Sets Syst..

[20]  Francisco Herrera,et al.  A Consensus Model for Group Decision Making With Incomplete Fuzzy Preference Relations , 2007, IEEE Transactions on Fuzzy Systems.

[21]  Francisco Herrera,et al.  Group decision making with incomplete fuzzy linguistic preference relations , 2009, Int. J. Intell. Syst..

[22]  Enrique Herrera-Viedma,et al.  Managing the consensus in group decision making in an unbalanced fuzzy linguistic context with incomplete information , 2010, Knowl. Based Syst..

[23]  Gloria Bordogna,et al.  A linguistic modeling of consensus in group decision making based on OWA operators , 1997, IEEE Trans. Syst. Man Cybern. Part A.

[24]  E. Herrera‐Viedma,et al.  Evaluating the Informative Quality of Documents in SGML Format Using Fuzzy Linguistic Techniques Based on Computing with Words , 2001 .

[25]  J. Kacprzyk,et al.  A ‘soft’ measure of consensus in the setting of partial (fuzzy) preferences , 1988 .

[26]  Tetsuzo Tanino,et al.  Fuzzy Preference Relations in Group Decision Making , 1988 .

[27]  Francisco Herrera,et al.  Theory and Methodology Choice functions and mechanisms for linguistic preference relations , 2000 .

[28]  R. Yager Families of OWA operators , 1993 .

[29]  Francisco Herrera,et al.  Linguistic measures based on fuzzy coincidence for reaching consensus in group decision making , 1997, Int. J. Approx. Reason..

[30]  Francisco Herrera,et al.  A Sequential Selection Process in Group Decision Making with a Linguistic Assessment Approach , 1995, Inf. Sci..

[31]  Enrique Herrera-Viedma,et al.  A quality evaluation methodology for health-related websites based on a 2-tuple fuzzy linguistic approach , 2010, Soft Comput..

[32]  Francisco Herrera,et al.  A Fuzzy Linguistic Methodology to Deal With Unbalanced Linguistic Term Sets , 2008, IEEE Transactions on Fuzzy Systems.

[33]  Francisco Herrera,et al.  Multiperson decision-making based on multiplicative preference relations , 2001, Eur. J. Oper. Res..

[34]  Francisco Herrera,et al.  Integrating three representation models in fuzzy multipurpose decision making based on fuzzy preference relations , 1998, Fuzzy Sets Syst..

[35]  Francisco Herrera,et al.  Aggregation operators for linguistic weighted information , 1997, IEEE Trans. Syst. Man Cybern. Part A.

[36]  Francisco Herrera,et al.  Group Decision-Making Model With Incomplete Fuzzy Preference Relations Based on Additive Consistency , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[37]  Enrique Herrera-Viedma,et al.  Evaluating the informative quality of documents in SGML format from judgements by means of fuzzy linguistic techniques based on computing with words , 2003, Inf. Process. Manag..

[38]  Luis Martínez-López,et al.  An Adaptive Consensus Support Model for Group Decision-Making Problems in a Multigranular Fuzzy Linguistic Context , 2009, IEEE Transactions on Fuzzy Systems.

[39]  J. Kacprzyk,et al.  Consensus Under Fuzziness , 2012 .

[40]  Francisco Herrera,et al.  A consensus model for multiperson decision making with different preference structures , 2002, IEEE Trans. Syst. Man Cybern. Part A.

[41]  Francisco Herrera,et al.  A web based consensus support system for group decision making problems and incomplete preferences , 2010, Inf. Sci..

[42]  Enrique Herrera-Viedma,et al.  A Consensus Model for Group Decision-Making Problems with Interval Fuzzy Preference Relations , 2012, Int. J. Inf. Technol. Decis. Mak..

[43]  Lotfi A. Zadeh,et al.  The concept of a linguistic variable and its application to approximate reasoning-III , 1975, Inf. Sci..

[44]  Zeshui Xu,et al.  Note on “Some models for deriving the priority weights from interval fuzzy preference relations” , 2008 .

[45]  Francisco Herrera,et al.  Individual and Social Strategies to Deal with Ignorance Situations in Multi-Person Decision Making , 2009, Int. J. Inf. Technol. Decis. Mak..

[46]  Enrique Herrera-Viedma,et al.  A Review on Information Accessing Systems Based on Fuzzy Linguistic Modelling , 2010 .

[47]  Enrique Herrera-Viedma,et al.  A model of an information retrieval system with unbalanced fuzzy linguistic information , 2007, Int. J. Intell. Syst..

[48]  Enrique Herrera-Viedma,et al.  Analyzing consensus approaches in fuzzy group decision making: advantages and drawbacks , 2010, Soft Comput..

[49]  Enrique Herrera-Viedma,et al.  A Note on Two Methods for Estimating Missing Pairwise Preference Values , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[50]  David Ben-Arieh,et al.  Linguistic-labels aggregation and consensus measure for autocratic decision making using group recommendations , 2006, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[51]  Francisco Herrera,et al.  Cardinal Consistency of Reciprocal Preference Relations: A Characterization of Multiplicative Transitivity , 2009, IEEE Transactions on Fuzzy Systems.

[52]  Ronald R. Yager,et al.  On ordered weighted averaging aggregation operators in multicriteria decisionmaking , 1988, IEEE Trans. Syst. Man Cybern..

[53]  Francisco Herrera,et al.  A note on the internal consistency of various preference representations , 2002, Fuzzy Sets Syst..

[54]  Zeshui Xu,et al.  On Compatibility of Interval Fuzzy Preference Relations , 2004, Fuzzy Optim. Decis. Mak..

[55]  Enrique Herrera-Viedma,et al.  Recommending biomedical resources: A fuzzy linguistic approach based on semantic web , 2010, Int. J. Intell. Syst..

[56]  Francisco Herrera,et al.  A model of consensus in group decision making under linguistic assessments , 1996, Fuzzy Sets Syst..

[57]  Francisco Herrera,et al.  A rational consensus model in group decision making using linguistic assessments , 1997, Fuzzy Sets Syst..

[58]  Yunliang Jiang An approach to group decision making based on interval fuzzy preference relations , 2007 .

[59]  Enrique Herrera-Viedma,et al.  A Selection Process Based on Additive Consistency to Deal with Incomplete Fuzzy Linguistic Information , 2010, J. Univers. Comput. Sci..