Interval-valued intuitionistic hesitant fuzzy entropy based VIKOR method for industrial robots selection

Abstract

In this paper, we proposed interval valued intuitionistic hesitant fuzzy entropy for determine the importance of the criteria and interval valued intuitionistic hesitant fuzzy VIKOR method for ranking the alternatives. Industrial Robots are utilized to perform complicated and hazardous tasks accurately and also used to enhance the quality and efficiency of the work. Selecting an industrial robot for performing a particular task depends on the work and the associated criteria of the robot. The materials handled by the robots are different like powdered, adhesive, bulky, brittle etc. In this manner, choosing a suitable robot from the set of available industrial robots to handle a particular material is a challenging task. To get a more conscionable decision result, a decision organization contains a lot of decision makers. The interval- valued intuitionistic hesitant fuzzy set is utilized as a competent mathematical tool for enunciate individuals hesitant thinking. An interval- valued intuitionistic hesitant fuzzy set (IVIHFS) concedes a set of several possible interval- valued intuitionistic fuzzy membership and non- membership values. Finally, the proposed interval- valued intuitionistic hesitant fuzzy entropy and VIKOR techniques utilized for industrial robot selection.