Multi-attribute group decision-making method based on weighted partitioned Maclaurin symmetric mean operator and a novel score function under neutrosophic cubic environment

Neutrosophic cubic set is the generalized version of neutrosophic sets and interval sets. It can deal with complex information by combining (NS) (CS). Maclaurin symmetric mean operator a classical aggregation in modern fusion theory. Partitioned MSM reflect interrelationships among attributes same partition, but different partitions are irrelevant. In order to efficiently gather NCS where partition relevant irrelevant, we extend PMSM environment define partitioned (NCPMSM) weighted operator. Later, overcome drawbacks existing score functions effectively distinguish two NCSs, novel function NCS. Next, based on NCWPMSM function, develop multi-attribute group decision-making method. Finally, give an example supplier selection illustrate usefulness proposed MAGDM. At time, comparative analysis show effectiveness advantages method compared methods.