Fermatean fuzzy Archimedean Heronian Mean-Based Model for estimating sustainable urban transport solutions

Abstract

Public transportation frameworks assume a critical role in the metropolitan region, especially in huge urban communities, where they offer a feasible answer for easing gridlock, moderating commotion contamination, and diminishing CO2 discharges. This paper presents some novel Fermatean fuzzy Heronian mean operators based on Archimedean t-norms, specifically the generalized Fermatean fuzzy Archimedean Heronian mean (GFFAHM) and the Fermatean fuzzy Archimedean geometric Heronian mean (FFAGHM). The study investigates different unique instances of these operators while exploring their essential properties. Besides, a powerful multiattribute decision-making (MADM) method is developed using the proposed operators. This approach offers a key asset for handling complex decision-making problems. Overcoming the capabilities of conventional BM operators, the GFFAHM and FFAGHM operators effectively minimize the potential redundancy in interrelationships during the decision-making process. The inclusion of the flexible parameters ρ and ϕ, which have a big impact on the decision-making process’ outcomes, increases the adaptability and resilience of the Archimedean t-based operators. To depict the feasibility of the proposed MADM method, a thorough quantitative model is introduced, outlining its useful execution. Through an exhaustive case study, the predominance of the proposed approach over existing strategies is experimentally established. Remarkably, the study uncovers that reducing fares is the most compelling factor in expanding the public transport framework, subsequently advancing sustainable urban transport. This study’s findings provide useful insights into decision-making processes and practical implications for policymakers, allowing them to make informed and impactful changes to the public transportation system. The proposed MADM method can play a vital role in upgrading the public transport framework, making way for remarkable strategy interventions in urban transport sustainability.