Dynamic interactive group decision making method on two-dimensional language
This addresses decision-making for groups needing multi-attribute evaluations, but it is incremental as it extends existing methods to two-dimensional and dynamic contexts.
The paper tackles the problem of group decision making by proposing a dynamic method based on two-dimensional linguistic information, which aggregates preferences using DULGWA operators and uses dynamic information entropy for attribute weights, with an example verifying its effectiveness.
The language evaluation information of the interactive group decision method at present is based on the one-dimension language variable. At the same time, multi-attribute group decision making method based on two-dimension linguistic information only use single-stage and static evaluation method. In this paper, we propose a dynamic group decision making method based on two-dimension linguistic information, combining dynamic interactive group decision making methods with two-dimensional language evaluation information The method first use Two-Dimensional Uncertain Linguistic Generalized Weighted Aggregation (DULGWA) Operators to aggregate the preference information of each decision maker, then adopting dynamic information entropy method to obtain weights of attributes at each stage. Finally we propose the group consistency index to quantify the termination conditions of group interaction. One example is given to verify the developed approach and to demonstrate its effectiveness