Signed distance-based closeness coefficients approach for solving inverse non-linear programming models for multiple criteria group decision-making using interval Type-2 pythagorean fuzzy numbers

Abstract

Pythagorean fuzzy sets (PFS) are extensively used to deal with ambiguity, vagueness and imprecision in real-world applications. In this article, interval type-2 Pythagorean fuzzy sets (IT2PFS) have been introduced that noticeably increases their flexibility as they are more effective in dealing with uncertainties. IT2PFS provide us with some extra degrees of freedom to characterize the vagueness and fuzziness of existent world. The novelty of the proposed scheme is to initiate an efficient approach for managing multiple criteria group decision-making (MCGDM) problems with partially known criterion weights modeled as interval type-2 trapezoidal Pythagorean fuzzy numbers (IT2TrPFN). Hybrid averaging (HA) operation based on weighted averaging (WA) and ordered weighted averaging (OWA) operators areemployed for constructing a collective decision environment by involving multiple decision-makers. Afterwards, an integrated optimization model based on a novel signed distance-based closeness coefficients (SDBCC) approach is established to approximate the importance weights of criteria and priority ranking of alternatives. The proposed scheme is employed for the selection of new site for building construction to demonstrate its feasibility and practicality. Moreover, a comparative investigation with some well-known approaches is conducted to verify the efficiency and usefulness of the proposed method © 2021 Elsevier B.V., All rights reserved.