Adaptive Algorithm for Adjusting Weights in Multiple Attributes Group Decision Making

Abstract

This paper studies weight adjustment in multiple attributes group decision making model. Firstly, the attribute weights respectively calculated by methods of AHP and entropy are optimized based on objective programming model. Secondly, the initial weights of decision-makers are updated by the grey correlation degree between the individual decision results and the group decision results. Furtherly, the group decision results are updated. Then the weight-adjusting is continued on the basis of the new group decision results. Based on 2-Norm Minkowski measure, the steady weights of decision-makers and final results of the group are gotten with the process of adjustment. Finally, a numerical example to evaluate wind power equipment supplier shows the feasibility and practicability of the proposed algorithm.