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A recursive group decision-making procedure for choosing qualified individuals

2009; Wiley; Volume: 24; Issue: 8 Linguagem: Inglês

10.1002/int.20365

1098-111X

Miguel A. González Ballester, José Luis Garcı́a-Lapresta,

Fuzzy Systems and Optimization

International Journal of Intelligent SystemsVolume 24, Issue 8 p. 889-901 Research Article A recursive group decision-making procedure for choosing qualified individuals Miguel A. Ballester, Miguel A. Ballester [email protected] Departament d'Economia i d'Història Econòmica, Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, SpainSearch for more papers by this authorJosé Luis García-Lapresta, Corresponding Author José Luis García-Lapresta [email protected] Departamento de Economía Aplicada, Universidad de Valladolid, Avda. Valle de Esgueva 6, 47011 Valladolid, SpainDepartamento de Economía Aplicada, Universidad de Valladolid, Avda. Valle de Esgueva 6, 47011 Valladolid, SpainSearch for more papers by this author Miguel A. Ballester, Miguel A. Ballester [email protected] Departament d'Economia i d'Història Econòmica, Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona, SpainSearch for more papers by this authorJosé Luis García-Lapresta, Corresponding Author José Luis García-Lapresta [email protected] Departamento de Economía Aplicada, Universidad de Valladolid, Avda. Valle de Esgueva 6, 47011 Valladolid, SpainDepartamento de Economía Aplicada, Universidad de Valladolid, Avda. Valle de Esgueva 6, 47011 Valladolid, SpainSearch for more papers by this author First published: 12 May 2009 https://doi.org/10.1002/int.20365Citations: 9AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Abstract In this paper, we introduce a new group decision procedure that follows a recursive pattern. In the first stage, the members of a group show their opinions on all the individuals of that group, regarding a specific attribute, by means of assessments within the unit interval. Taking into account this information, some aggregation operators and a family of thresholds, a subgroup of individuals is selected: Those members whose collective assessment reach a specific threshold. Now only the opinions of this qualified subgroup are taken into account, and a new subgroup emerges in the implementation of the aggregation phase. We analyze when this recursive procedure converges providing a final subgroup of qualified members, taking into account some extended ordered weighted averaging operators. © 2009 Wiley Periodicals, Inc. References 1 Kasher A, Rubinstein A. On the question "Who is a J?". A social choice approach. Logique Analyse 1997; 160: 385– 395. 2 Samet D, Schmeidler D. Between liberalism and democracy. J Econ Theory 2003; 110: 213– 233. 3 Fodor J, Roubens M. Fuzzy preference modelling and multicriteria decision support. Dordrecht, The Netherlands: Kluwer Academic Publishers; 1994. 4 Grabisch M, Orlovski SA, Yager RR. Fuzzy aggregation of numerical preferences. In: R Slowinski, editor. Fuzzy sets in decision analysis, operations and statistics. Boston, MA: Kluwer Academic Publishers; 1998. pp 31– 68. 5 Calvo T, Kolesárova A, Komorní ková M, Mesiar R. Aggregation operators: properties, classes and construction methods. In: T Calvo, G Mayor, R Mesiar, editors. Aggregation Operators: New trends and applications. Heidelberg, Germany: Physica-Verlag; 2002. pp 3– 104. 6 Ballester MA, Garcí a-Lapresta JL. A model of elitist qualification. Group Decision Negotiation 2008; 17: 497– 513. 7 Ballester MA, Garcí a-Lapresta JL. Sequential consensus for selecting qualified individuals of a group. Int J Uncertainty, Fuzziness Knowledge-Based Syst 2008; 16: 57– 68. 8 Yager RR. Ordered weighted averaging operators in multicriteria decision making. IEEE Trans Syst, Man Cybern 1988; 8: 183– 190. 9 RR Yager, J Kacprzyk (editors). The ordered weighted averaging operators: Theory and applications. Norwell, MA: Kluwer Academic Publishers; 1997. 10 Mayor G, Calvo T. On extended aggregation functions. In: Proc of IFSA 97, Prague; 1997. Vol. I, pp 281– 285. 11 Calvo T, Mayor G. Remarks on two types of extended aggregation functions. Tatra Mountains Math Pub 1999; 16: 235– 253. 12 Herrera F, Herrera-Viedma E. Aggregation operators for linguisting weighted information. IEEE Trans Systems, Man Cybern, Part A: Syst Humans 1997; 27: 646– 656. 13 Herrera F, Herrera-Viedma E, Verdegay JL. Direct approach processes in group decision making using linguistic OWA operators. Fuzzy Sets Syst 1996; 79: 175– 190. Citing Literature Volume24, Issue8August 2009Pages 889-901 ReferencesRelatedInformation