An Integrated Bayesian Best-Worst Method and Consensus-Based Intuitionistic Fuzzy Evaluation Based on Distance from Average Solution Approach for Evaluating Alternative Aircraft Models from a Sustainability Perspective

Abstract

Sustainability in transportation is vital for lessening environmental effects and ensuring the long-term viability of the transportation industry. The aviation sector, a significant player in sustainable transport, has encountered obstacles in reducing its ecological footprint, especially in aircraft design and operation. Symmetry and asymmetry exist widely in the aviation sector, as in other industrial applications. Multicriteria decision making (MCDM) is an important research topic that is widely applied to practical decision-making problems and is considered a complex tool with which to balance the symmetry between goals and conflicting criteria. This research assesses different airplane models in order to pinpoint the most environmentally friendly options using the Bayesian best-worst (BWM) method for evaluating criteria and the consensus-based intuitionistic fuzzy evaluation based on distance from average solution (IF EDAS) method for assessing alternatives. The Bayesian BWM approach facilitates group decision making on criteria evaluation and systematically evaluates factors like fuel efficiency, emissions, and noise levels, offering a holistic view of each airplane model's sustainability performance. Conversely, consensus-based IF EDAS allows for the ranking of alternatives based on their distance to the average solution for a sustainable airplane model while concurrently considering multiple criteria, guiding decisionmakers to a consensus and eliminating the asymmetry between opinions before the final decision. This study reveals that technical features are the critical criteria for airplanes and significantly influence alternative rankings. The findings indicate that the chosen decision criteria greatly impact the selection of the most sustainable airplane model as part of a sustainable transportation system, potentially altering ranking orders.