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Sustainable urban mobility systems with CRITIC-CIMAS-WASPAS approach using intuitionistic fuzzy credibility numbers

algorithms-and-analysis-of-algorithms
computer-education
data-science

Abstract

This paper presents a novel concept of algebraic structures for intuitionistic fuzzy credibility numbers (IFCNs) to effectively handle uncertainty in multi-criteria decision-making (MCDM) problems. It extends the IFCS concept to intuitionistic fuzzy credibility ideals (IFCIs) in BCK-algebras. Operational laws for IFCSs, such as inclusion, sum, and product, are developed to address uncertain information in the MCDM process. A robust hybrid MCDM framework, termed CRITIC-CIMAS-WASPAS, is proposed. The criterion importance assessment (CIMAS) method calculates objective weights by summing performance ratios across criteria. The CRITIC method adjusts subjective criterion weights based on the correlation and variability of criteria. The weighted aggregated sum product assessment (WASPAS) method is extended to CIFCSs to classify and rank the alternatives more accurately and efficiently. The proposed framework is applied to optimize urban mobility systems, encompassing ride-sharing, autonomous vehicles, scheduling, and fare collection. Various validation tests demonstrate the reliability of this hybrid approach in determining optimal and reasonable decisions that are acceptable to experts and stakeholders.
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