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A goal programming model for incomplete interval multiplicative preference relations and its application in group decision-making


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  • Liu, Fang
  • Zhang, Wei-Guo
  • Wang, Zhong-Xing
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    In decision making problems, there may be the cases where the decision makers express their judgements by using preference relations with incomplete information. Then one of the key issues is how to estimate the missing preference values. In this paper, we introduce an incomplete interval multiplicative preference relation and give the definitions of consistent and acceptable incomplete ones, respectively. Based on the consistency property of interval multiplicative preference relations, a goal programming model is proposed to complement the acceptable incomplete one. A new algorithm of obtaining the priority vector from incomplete interval multiplicative preference relations is given. The goal programming model is further applied to group decision-making (GDM) where the experts evaluate their preferences as acceptable incomplete interval multiplicative preference relations. An interval weighted geometric averaging (IWGA) operator is proposed to aggregate individual preference relations into a social one. Furthermore, the social interval multiplicative preference relation owns acceptable consistency when every individual one is acceptably consistent. Two numerical examples are carried out to show the efficiency of the proposed goal programming model and the algorithms.

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    Bibliographic Info

    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 218 (2012)
    Issue (Month): 3 ()
    Pages: 747-754

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    Handle: RePEc:eee:ejores:v:218:y:2012:i:3:p:747-754

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    Keywords: Goal programming model; Consistency; Group decision-making; Incomplete interval multiplicative preference relation; IWGA operator;


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    1. S. Alonso & E. Herrera-Viedma & F. Chiclana & F. Herrera, 2009. "Individual And Social Strategies To Deal With Ignorance Situations In Multi-Person Decision Making," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 8(02), pages 313-333.
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    3. Michele Fedrizzi & Silvio Giove, 2006. "Incomplete pairwise comparison and consistency optimization," Working Papers 144, Department of Applied Mathematics, Università Ca' Foscari Venezia.
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    Cited by:
    1. Fernandez, Eduardo & Olmedo, Rafael, 2013. "An outranking-based general approach to solving group multi-objective optimization problems," European Journal of Operational Research, Elsevier, vol. 225(3), pages 497-506.
    2. Liu, Fang & Zhang, Wei-Guo & Zhang, Li-Hua, 2014. "Consistency analysis of triangular fuzzy reciprocal preference relations," European Journal of Operational Research, Elsevier, vol. 235(3), pages 718-726.
    3. Bustince, H. & Jurio, A. & Pradera, A. & Mesiar, R. & Beliakov, G., 2013. "Generalization of the weighted voting method using penalty functions constructed via faithful restricted dissimilarity functions," European Journal of Operational Research, Elsevier, vol. 225(3), pages 472-478.
    4. Cabrerizo, Francisco Javier & Herrera-Viedma, Enrique & Pedrycz, Witold, 2013. "A method based on PSO and granular computing of linguistic information to solve group decision making problems defined in heterogeneous contexts," European Journal of Operational Research, Elsevier, vol. 230(3), pages 624-633.


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