A Discriminative Dynamic Index Based on Bipolar Aggregation Operators for Supporting Dynamic Multi-criteria Decision Making

  • Yeleny ZuluetaEmail author
  • Juan Martínez-Moreno
  • Luis Martínez
  • Macarena Espinilla
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 228)


While Multi-Criteria Decision Making (MCDM) models are focus on selecting the best alternative from a finite number of feasible solutions according to a set of criteria, in Dynamic Multi-Criteria Decision Making (DMCDM) the selection process also takes into account the temporal performance of such alternatives during different time periods. In this contribution is proposed a new discriminative dynamic index to handling differences in temporal behavior of alternatives, which are not discriminated in preceding dynamic approaches. An example is provided to illustrate the feasibility and effectiveness of the proposed index.


Aggregation Function Aggregation Operator Dynamic Index Associativity Property Resolution Procedure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Yeleny Zulueta
    • 1
    Email author
  • Juan Martínez-Moreno
    • 2
  • Luis Martínez
    • 2
  • Macarena Espinilla
    • 2
  1. 1.Carretera San Antonio de los BañosUniversity of Informatics ScienceHavanaCuba
  2. 2.University of JaenJaenSpain

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