Multiple attribute decision making using hesitant triangular fuzzy sets

Abstract

Multiple attribute decision making (MADM) is an inevitable part of our daily life which is immensely used in managerial, economics, constructional problems, etc. In real world, there are many situations where one has to take a decision in a highly uncertain environment. In that case of decision making, since a linguistic term is closer to human cognitive process, it is more convenient and realistic for the decision maker to provide his assessment in linguistic form. Nevertheless, sometimes the decision maker cannot easily provide a single linguistic term as an expression of his knowledge about a particular outcome. The current study presents an extension of technique for order preference by similarity to ideal solution (TOPSIS) using hesitant triangular fuzzy sets (HTFS) to solve MADM problems. Herein, the importance weight of different attributes and the rating of alternatives based on these attributes by the decision maker are considered to be HTFS. The proposed technique is demonstrated by taking an example of supplier selection in supply chain management for a fertilizer making industry. The linguistic terms such as Very low (VL), Low (L), Medium (M), High (H) and Very high (VH) are used to be the constituent of HTFS representing the importance weight of attributes. And, linguistic terms such as Very poor (VP), Poor (P), Fair (F), Good (G) and Very good (VG) will constitute the HTFS representing the rating of different alternatives under the given set of attributes in a MADM problem.