Optimization of transportation efficiency through fuzzy logic and LINGO software

This paper proposes a new approach to optimize transportation efficiency by integrating fuzzy logic with a multi-objective stratified sampling framework using the LINGO software. Intuitionistic fuzzy programming and randomized response techniques have been adapted in this proposed methodology to overcome data privacy, cost-effectiveness, and minimization of variation within strata problems. The model was confirmed to be able to lower standard errors, maintain data integrity, and improve transportation management in computational tests. This study significantly contributes to the development of optimization algorithms and transportation systems with a solid basis for accurate, privacy-preserving data collection and efficient decision-making.