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

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 .