Methods of Aggregation of Expert Opinions in the Framework of Intelligent Products

Intelligent products may be considered as information vectors, conveying their own information from a phase of its life cycle to another. Considering that such a product could be made with “communicating material”, in previous work, a data dissemination process has been developed with the aim of selecting information from a database, that should be stored on the product according to the current stage of its life cycle. This selection is based on an indicator of relevance which depends on a multitude of criteria, whose weights are evaluated by a group of experts. The set of expert opinions must be formalized in accordance with a mathematical theory and then, synthesized by a suitable aggregation method. In this framework, three aggregation methods are introduced and compared. This comparison is carried out based on the scenario of data dissemination when using intelligent products. Results enable to assess the goodness of fit of the three aggregation methods.

[1]  E. Rondeau,et al.  A fuzzy analytic hierarchy process for group decision making: Application for embedding information on communicating materials , 2012, CCCA12.

[2]  Sylvain Kubler,et al.  Information dissemination process for context-aware products , 2012 .

[3]  Didier Dubois,et al.  A review of fuzzy set aggregation connectives , 1985, Inf. Sci..

[4]  Duncan C. McFarlane,et al.  Intelligent Products in the Supply Chain - 10 Years on , 2013, Service Orientation in Holonic and Multi Agent Manufacturing and Robotics.

[5]  R. Cooke Experts in Uncertainty: Opinion and Subjective Probability in Science , 1991 .

[6]  V. Agarwal,et al.  The intelligent product driven supply chain , 2002, IEEE International Conference on Systems, Man and Cybernetics.

[7]  Sylvain Kubler,et al.  Embedding Information on Communicating Materials from Context-Sensitive Information Analysis Based on Fuzzy AHP Theory , 2012, 2012 IEEE International Conference on Green Computing and Communications.

[8]  Didier Dubois,et al.  Aggregation of expert opinions and uncertainty theories , 2006 .

[9]  Hsuan-Shih Lee,et al.  Optimal consensus of fuzzy opinions under group decision making environment , 2002, Fuzzy Sets Syst..

[10]  Enrique Herrera-Viedma,et al.  A statistical comparative study of different similarity measures of consensus in group decision making , 2013, Inf. Sci..

[11]  Daniel T. Larose,et al.  Discovering Knowledge in Data: An Introduction to Data Mining , 2005 .

[12]  Jan Holmström,et al.  Intelligent Products: A survey , 2009, Comput. Ind..

[13]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .