An optimal aggregation method for interval grey numbers using on Steiner-Weber point with application

Abstract

Aiming at the problem of low accuracy of two-dimensional preference information aggregation, this paper takes two-dimensional interval grey numbers as an example to define its preference information mapping rules. This rule maps preference information to preference points on a two-dimensional plane. Based on the theory of plane Steiner-Weber point, we construct a two-dimensional optimal model, and prove the optimality of the model theoretically. Then, adopt plant growth simulation algorithm (PGSA) to solve the proposed model. The obtained optimal aggregation point that can represent the comprehensive opinions. Finally, by analyzing the selection problem of Fangcang shelter hospital and comparing it with the particle swarm optimization (PSO) method, we conclude that the sum of weighted Euclidean distance obtained by our method is minimal. The aggregation precision of our method is higher than that of other aggregation method to a certain extent.