Novel Concepts of Soft Multi Rough Sets with MCGDM for the Selection of Humanoid Robot

Abstract

This paper comes out with a fascinating fusion of soft sets, multisets and rough sets. We introduce novel concepts of soft multi rough sets (SMR-Sets) and soft multi approximation spaces. We present some fundamental properties of SMR-approximations and their related examples. We also discuss the variation between some properties of Pawlak approximation space, soft approximation spaces and the same properties of soft multi approximation spaces. Furthermore, we present two different algorithms based on soft multi rough set with an application to multi-criteria group decision-making (MCGDM) for the selection of humanoid robot.