A study on mu/ti-crit~r B gr[]op decision making techniques based onluzzy and quanttfative information

Abstract

Decision making activities are prevalent in the human race. Till date, numerous multi-criteria group decision making (MCGDM) techniques have been put forward under various fuzzy con texts to address scenarios of vague nature. However, there are some imperfections in these developed studies. The present work mainly aims to remove the existing limitations and to construct some robust MCGDM techniques in order to tackle the complex problems more ac curately. For this, we revise the basic operational laws, comparison method and a series of ag gregation operators for the probabilistic uncertain linguistic term set (PULTS) and uncertain probabilistic linguistic term set (UPLTS). In addition, some innovative fuzzy tools, namely probabilistic hesitant intuitionistic linguistic term set (PHILTS) and weighted interval-valued dual hesitant fuzzy set (WIVDHFS), and their related theories, are introduced. Then, based on the proposed theory, some well-known MCGDM techniques, viz. technique of order pref erence similarity to the ideal solution (TOPSIS), gained and lost dominance score (GLDS), weighted aggregated sum product assessment (WASPAS) and aggregation-based method are extended to more generalized fuzzy frameworks. Meanwhile, several criteria weight determi nation models are built according to different fuzzy environments. To validate the practicality of the proposed work, we address some real world problems, including investment problem, supplier selection and teaching quality assessment. Further, to testify the potentiality and weaknesses of the provided techniques, comparative study and sensitivity analysis are also delineated