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

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. © 2023 Elsevier Ltd

A large-scale group decision making method based on spatial information aggregation and empathetic relationships of experts

Large-scale group decision making (LSGDM) involving a large number of experts has attracted more and more scholars' attention. Many LSGDM methods assumed that experts were independent to make evaluations, but the development of social media promotes the communication among experts, which makes experts no longer independent. In addition, existing LSGDM methods mainly adopted aggregation strategies such as the weighted average operator and arithmetic average operator to integrate the opinion of experts in a cluster, which makes the aggregation results cannot reflect the real opinion of the expert group. To address these issues, considering the empathetic network of experts, this study proposes an LSGDM method based on a new aggregation method for expert space information. Firstly, we determine objective weights of experts according to the objective empathetic relationships among experts. Then, the Steiner-Weber point problem is used as a prototype to establish an aggregation method called the spatial optimal aggregation (SOA) method to fuse the spatial information of experts. The model is solved by the genetic algorithm. Finally, an illustrative example about the selection of the most urgent risk in the transportation of COVID-19 vaccines is presented to show the validity and practicability of the proposed model. © 2023 Elsevier Inc.