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Genetic Algorithms (GAs) have emerged as a robust optimization technique within civil engineering, particularly in the design of concrete mix proportions. Their inherent ability to address complex, multi-objective, and nonlinear optimization problems makes them well-suited for this application. Conventional mix design methodologies often rely on iterative, trial-and-error approaches that are both time-consuming and may fail…