Optimized model involving forward and inverse problem formulation for the assessment of environmentally sustainable transportation alternatives based on intuitionistic linguistic weighted average

Abstract

Intuitionistic fuzzy set theory provides a versatile framework for conveying information acquired during the decision-making process, particularly adept at handling indeterminate data. This study aims to devise a robust alpha-cut approach for intuitionistic linguistic weighted average (ILWA) applied specifically to intuitionistic fuzzy numbers (IFN). The utilization of an extended Jaccard Similarity Measure (EJSM) within the intuitionistic fuzzy context will yield valuable insights into the accuracy of representing linguistic data through the ILWA method. These advancements hold significant implications for selecting environmentally sustainable transportation alternatives and furnish analytical techniques for addressing uncertainty and imprecision across diverse decision- making domains.