An advanced approach to multiple criteria optimization and compromise solutions under circular intuitionistic fuzzy uncertainty

Abstract

The intention of this work is to create an advanced VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) approach that deals with multiple criteria optimization and compromise solutions in the face of circular intuitionistic fuzzy (C-IF) uncertainty. There has been limited research on enhancing VIKOR techniques to manipulate multiple criteria decision analysis (MCDA) with sophisticated C-IF information. Specifically, the relative score function in current C-IF VIKOR methods loses its meaning when the radius of the C-IF number is zero, restricting its applicability to regular intuitionistic fuzzy contexts. Furthermore, converting C-IF information into intuitionistic fuzzy contents prematurely using existing C-IF VIKOR algorithms results in inadequate preservation of the C-IF connotation, hindering the primary objective of using C-IF theory to manage MCDA issues. This study addresses the limitations of the current relative score system in C-IF contexts and recommends a more legitimate and fair scoring function. The upgraded C-IF scoring function includes scaling and exponential parameters, making it more pragmatic and adaptable than the present relative scoring mechanism. By connecting the suggested C-IF scoring function with the recently published C-IF Minkowski distance measurements, the study establishes a parameterized C-IF VIKOR methodology to analyze MCDA issues arising from C-IF uncertainty. The suggested parameterized C-IF VIKOR model provides accessible assessments of individual regret, collective utility, and trade-off indices by utilizing three- and four-term C-IF metric ratios. The model constructs a synthesized mechanism to investigate the requirements for acceptable advantage and decision-making stability for locating agreeable compromise solutions. The viability and performance of the suggested technique are manifested through applications in waste disposal location selection, multi-expert supplier evaluation, and medical waste disposal techniques. Comparative analysis is executed to highlight implications for theory, practice, and future research. This study provides significant contributions, including (i) an innovative approach to the C-IF VIKOR methodology for broadening the coverage of higher-order fuzzy research models, (ii) a new C-IF scoring function for decision aiding to overcome the limitation of the current relative score function, and (iii) a novel conceptual framework of a parameterized VIKOR for empowering decision-makers with more leeway in adapting the VIKOR solution to intuitively judged outcomes.