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

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.

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