Solving robot selection problem by a new interval-valued hesitant fuzzy multi-attributes group decision method

Abstract

‎Selecting the most suitable robot among their wide range of specifications and capabilities is an important issue to perform the hazardous and repetitive jobs‎. ‎Companies should take into consideration powerful group decision-making (GDM) methods to evaluate the candidates or potential robots versus the selected attributes (criteria)‎. ‎In this study‎, ‎a new GDM method is proposed by utilizing the complex proportional assessment method under interval-valued hesitant fuzzy (IVHF)-environment‎. ‎In the proposed method‎, ‎a group of experts is established to evaluate the candidates or alternatives among the conflicted attributes‎. ‎In addition‎, ‎experts assign their preferences and judgments about the rating of alternatives and the relative importance of each attribute by linguistic terms which are converted to interval-valued hesitant fuzzy elements (IVHFEs)‎. ‎Also‎, ‎the attributes’ weights and experts’ weights are applied in procedure of the proposed interval-valued hesitant fuzzy group decision-making (IVHF-GDM) method‎. ‎Hence‎, ‎the experts’ opinions about the relative importance of each attribute are considered in determination of attributes’ weights‎. ‎Thus‎, ‎we propose a hybrid maximizing deviation method under uncertainty‎. ‎Finally‎, ‎an illustrative example is presented to show the feasibility of the proposed IVHF-GDM method and also the obtained ranking results are compared with a recent method from the literature‎.