Signed distance-based approach for multiple criteria group decision-making with incomplete information using interval type-2 neutrosophic numbers

In real life decision making situations, we are often provided with partial information where it is difficult analyze the objects under consideration. Instead of employing simple fuzzy sets, interval type-2 trapezoidal neutrosophic numbers can be used which have better representational power and ability to cope with uncertain situations. The approach discussed in this article is an effective tool for managing multiple criteria group decision-making situations with partially known criterion weights modelled as interval type-2 trapezoidal neutrosophic numbers. To aggregate of opinion of multiple decision-makers, a hybrid averaging operation based on weighted averaging and ordered weighted averaging (OWA) operations is employed for a collective decision environment. Partial information provided by different people is often inconsistent, therefore we have to construct certain optimized models involving deviation variables to deal with such inconsistencies. We propose such an integrated optimization model based on a new signed distance-based closeness coefficients approach to determine the weights of criteria and priority ranking of alternatives. Feasibility of the proposed technique is discussed with an implementation of patient centered medicine system for choosing the appropriate treatment method. Moreover, a comparative investigation with previous approaches is conducted to demonstrate the effectiveness of the given approach.